>>Hello, and welcome to the cubes. Continuous coverage of AWS reinvent 2021. I'm Dave Nicholson, and we're running an incredible event this year. One of the most important technology events. It's a hybrid event with two live stages. Two sets here in Las Vegas. Two studios we've interviewed more than a hundred guests and two distinguished guests that I have here from emphasis today have joined us. Thank you very much. Uh, Mr., who's the executive vice president of Infosys cobalt. And we'll talk about what that is exactly in a moment along with David Wilson, Wilson, I'm sorry, senior vice president and head of global alliances in the partner ecosystem for Infosys gentlemen. Welcome. Thank you. Thank you very much. So let's cut right to the chase cobalt. And when you tell your family that you're executive vice-president of cobalt, do they just smile and immediately nod? Like they know what it is? Absolutely. >>In fact, uh, in fact it is so exciting for us, uh, what we did at Infosys, just to define cobalt in one sentence, it is a set of services, solutions, and products that we are bringing together to solve, you know, accelerate our customer's journey or what we call as the customer's digital journey. So in slough, everybody talking about Kala cloud in a different way, with different narratives, different value proposition we had in forces. And by the way, we were the first ones in the world to combine all of this and the one brand called cobalt. So that's essentially what cobalt is. So anything and everything that we do in cloud, it's all under this brand called cobalt and that's Infosys cobalt. >>So does, does Infosys cobalt include a combination of bespoke solutions, cheering for people as well as packaged standardized things? How do you, how do you strike a balance because you can't have a one size fits all? Uh, what does that look like? How do you segregate those? >>Yes. Great question. So, so essentially what you are done with a cobalt is a delicate cobalt. In two ways. One is there are customers who want a solutions to solve technology problems. It could be getting out of data centers, it could be migrating workloads to cloud. It could be analytics on cloud ERP on cloud daddy's mainframe modernization, and, you know, getting off mainframes. And at the same time, there are industry verticals like financial services, retail manufacturing, and of course, life sciences, and many more who want to understand what are the business solutions and what are the solutions that we have for solving their business problems. So essentially cobalt is a bespoke solutions. It has products, it has platforms, and we have brought all of this together and we take it to our customers. So essentially these are industry blueprints. These are reference architectures. So we have 250 industry blueprints and around 25,000, that's it that we can actually take to our customers to help their digital journey. >>So, David, I imagine that key to the success of cobalt is, uh, uh, the idea of partnerships, talk about the alliances, uh, uh, that, uh, that you're involved with specifically the way that cobalt interacts with the AWS yes. >>Universe. Absolutely. So the, you know, as we designed our cobalt strategy, the partners are a major component of this. They contribute to it. They're part of the design. And ultimately when we go to the clients with these solutions, these assets, uh, our partners, components are baked right into the solution. In the case of AWS, we've been so successful with it that we recognize this week, uh, as their industry solutions partner of the year. Congratulations. Yeah. So I was joking. We should bring our trophy and put it in between, but we emphasis is invested heavily in developing the, the partner ecosystem, you know, gone are the days where our clients are, uh, putting out an RFP and purchasing individual piece parts, and then, you know, searching at NSI. They're looking for a business outcomes and, uh, uh, emphasis along with our cobalt strategy is able to work with partners like AWS and go there and sell an outcome and accelerate the whole. >>Well, you mentioned RFPs. Uh, what is your, uh, what is your go-to market strategy look like in terms of engaging with those end user clients? Um, is it in partnership with AWS? Is it led by Infosys bringing in AWS where appropriate some mix of the two? What does that look like in this world of cooperation and petition that we're in, >>It's actually a mix of two. So essentially the way we go to market is that there are solutions that Infosys has built on AWS that we will take to our customers. There are solutions that you have built, which are cloud neutral, and those are some things that we take to the customers. And the third one, which is very important is co-creating solutions for our customers along with AWS. So our go to market is a combination of all of them, and that's what makes it exciting. >>So a non-test running cobalt, you're, you're responsible for alliances. You guys are probably in contact a lot with one another. All of these crazy new things are announced at AWS. I'm sure you get a little bit of a preview of it. It's not a complete, it's not a complete surprise when you arrive, but you've gotta be screaming for teams and solutions to leverage some of the coolest stuff within cobalt. How does that, how does that conversation go? >>Yeah, so David David and I work very closely, right? In fact, uh, uh, the way, the way we do things is our go to market cannot be complete without partners. So similarly my strategy and our strategy and global cannot be complete without David. So we actually worked together to identify, in fact, we have been visiting a lot of boots. We got to create, we've gone to a lot of great ideas. We want to see how we can bring them into the cobalt framework and bundle some of that as part of our solutions. So we keep looking at those, we'll look at the announcements that were made and we'll solve, you know, identify many more sales motions that we can take to the, >>So David talk about some of the things you've seen here at re-invent this week that are specifically relevant for cobalt and emphasis customer. >>Well, what's some of the most exciting discussions we've been having is with, uh, not only, uh, AWS themselves about the, the announcements and the way in which we can leverage them, leverage them and go to market. But, uh, AWS has built out their own partner ecosystem, uh, that we then interact with. So we've had some exciting conversations with AWS's ISV partners, their, uh, their other solution providers about how we can bring this together and go to market together. You know, when, when an example, we had a lot of discussions this week was about, uh, how we're doing it, right? The mainframe services, uh, that were announced and how we can support them in building out our industry specific assets. So, you know, taking a kernel of what AWS provides and then wrapping our secret sauce around it, in partnership with other companies and then take into our clients, you know, that's what we're, I, it, the good part is we can quickly go from a discussion to a, go to market, a dialogue with our direct clients who are also here, which have been in real-time having those discussions. >>So emphasis a non has been a trusted advisor for clients predating the Dawn of cloud, if you will. Uh, and I'm sure that certain slices of your revenue don't wanna make this too uncomfortable. A question certain slices of your revenue are still dependent upon all of that. 80% of it. That's still on prem. How do you manage that? You're, you're laser focused on cobalt and you've got alliances. Um, everybody's looking towards the cloud. How do you balance that with the very real needs of Infosys as a business? Aren't you in the same boat as your customers, in terms of transformation? >>Well, you know, I, I would, I'm sorry, >>My eyes go back and forth. See, I told you it was gonna be easy for us to have a conversation. Yeah. Jump into >>W when you, when you look at the different partners out there, we have a discussion about being asset heavy asset light emphasis. Um, we, we grew up through application management, uh, and now as we're seeing these transformations go forward, the last thing we wanted to be is a server huggers. Uh, we're ready to accelerate these transformations as fast as possible. And, uh, you know, partners like AWS are recognizing that, uh, a non steam can go in there and be the disruptor to actually accelerate those transformation. >>Absolutely. In fact, involved when we spoke to some of the AWS executives, uh, we want to be the challenger, right? Because we don't carry any baggage. Uh, we clearly believe, as Gartner says that a cloud is going to be the, for business innovation, and we want to drive innovation and transformation for our customers. So essentially we want to make this relationship with AWS much bigger and better. We want to be the partners with our clients to drive business innovation with industry segments, industry clouds, solutions that drive opening, new markets, building better products and solutions, helping get better customer intimacy and those kinds of things. And so that's essentially what our thought processes with, uh, what we want to do. >>It's been mentioned a few times here that, uh, somewhere around 80 to 85% of it spend is still on premises. It's not in the cloud yet. So despite how large, we all think the AWS AWS universe has become so far, we're really just at the beginning stages. But what are you seeing in terms of clients hesitancy towards cloud at this point, has that changed over the last couple of years? Uh, what are the inhibiting factors that you see? What are the accelerants that you see at this stage of the game? >>Well, in fact, in fact, COVID unfortunately Colbert, uh, while it was all a very bad thing, but it actually helped accelerate customer's journey to cloud. Uh, in fact, uh, the, we have several customers who used to say that, you know, everybody has to come to office to work. Nobody can work remotely because there are security constraints that is, there will be impacted the security posture, but to when we hit March, 2020, and everybody had to work remote, it's the same set of customers who decided to go to cloud and started limited him to part of cloud. So I would say COVID in short has accelerated customers knowledge about cloud. They are no longer worried about security. They're no longer worried about, uh, latency and bandwidth. I think I don't see any major hesitancy at this point of time. Uh, but the trend that we're seeing towards cloud is cloud is going to be used more for innovation. And it's not just going to be about, take my data center and moving to cloud, right? So it's not going to be just those tactical reasons. Uh, and that's exactly what we did. We actually came out with a report, which says, moving from cloud chaos to cloud clarity, and it talks about all these facets of what are those strengths that customer should look for. So that's essentially what we use. >>So I imagine cobalt one of the kind of main ideas behind it is to remove friction associated with that move to cloud, to the extent that you can not be reinventing the wheel every single time you're engaging a customer. Is that, is that a fair statement? >>In fact, you know, many customers of ours, in fact, almost all of them are saying, we do not want to reinvent the wheel. So how can you help us? So what we have done as part of cobalt is to bring these reference architectures, right? So for example, if a financial services customer wants to fight fraud, fraud analytics is a reference architecture that we have. Uh, if the telco customer wants to implement 5g, we have a framework and a reference architecture for OSS BSS on cloud. Uh, if there is licenses customer who wants to basically look at drug discovery, we have an architecture for that. So we want to make it more and more in a inference architecture based without reinventing the wheel and bring the best practices from other customers to drive those scenarios. So that's essentially what we do. >>So cobalt underway, you've been recognized for a performance to this point. It's a lot of pressure for 2022. So what are you going to, what do you, what, what, what are you going to slap on the desk in 2022? When we get back together, >>We do plan to up bookends by this time next year, to, to able to pre >>It is perfectly acceptable by the way, to share both the 20, 21 and 2022 award on stage, because we have to make up for 2019 when we weren't here physically. >>But to build off of, with a, knotless saying about the, uh, you know, what's going on in the last 18 to 24 months, you know, we're seeing clients now that we have one that, uh, came to us with a 114 list of products that they bought from various partners, either directly through distributors and such and saying, listen, we no longer want to be in the procurement function. You know, we want to take these hundred and 14 products. We recognize we're going to get it down to 30 or 40 of the key ones, obviously a shifting a lot of that to cloud. And we were able to leverage emphasis cobalt to actually accelerate that and incorporate our partner components to help that shift. So I think next year, I think that will be a major theme that you're seeing clients recognize that the, the way in which they procure and they develop their it platform will be much different. And emphasis with the design we put in place will be in a key position to, to support them at that. Well, >>We recorded this. I'm not sure if you realized we were actually recording this, so we're going to go, we can go back and review this tape next year and we'll see. And I hope to see you then, David, thank you so much for joining us here at the cube and for the cube here in our continuous coverage at AWS reinvent 2021 live in Las Vegas. I'm Dave Nicholson saying stay tuned because there's always more on the cube. And I'd like to remind you that we are your leader in hybrid tech event coverage.

>> You're watching theCUBE. Welcome to our continuous coverage of AWS re-Invent 2021. I'm Dave Nicholson. We've got an amazing event that's been going on for the last four days with two live sets, two studios, more than 100 guests, and two very distinguished gentlemen here on the set with us live in Las Vegas. I'd like to welcome Krishna Mohan, Vice President and Global Head of TCS's AWS Business Unit. Welcome Krishna. >> Thank you Dave. >> Dave: And also with us Aditya Jagapal Nagarajan. >> Thank you. >> Dave: I hope I did your name justice. >> Perfect. >> Right, I tried. And Aditya is Head of Strategy and Business Operations for the TCS AWS Business Unit. Krishna, starting with you, tell us about TCS and AWS over the last year. What's been going on. >> Yeah. >> Thank you Dave for having me here. It's great to be in person actually, back in re-Invent, back in person, 25,000 people, but still we have pretty good measures, health measures that way. So I'm very happy to be here. TCS AWS business unit was formed three quarters back and we actually had always AWS partnership, but we actually felt that it's important to kind of have a separate business unit, which is the full stack, multi dimensional unit providing cloud migration modernization across applications, data, and infrastructure, and also main focus on industry solutions. So it has been a great three quarters, and our partnership only enhanced significantly, predominantly what we're actually seeing in the last one year. The cloud overall transformation, I think it kind of taken a different shape. It used to be cloud migration, modernization, cloud native development, but from there it has moved to enterprise transformation, that's happening on cloud, and specifically AWS majority of the time. So with that, we actually see a lot of customers. Broadly you can categorize them into three, cloud for IT, cloud for business, and cloud for innovation. And we're definitely seeing maximum traction there with our customers across the three categories. So I'm super excited to be here at the re-Invent, you know, a couple of our customers were in the keynote, Abort and Adam and Doug. In the Western Union was the keynote, Shelly covered at Western union transformation in the partner keynote with Doug, and very happy to see Linda Cower, the transformation in the United Headlines with Adam. So it's really great to see how we are helping the customers on the transformation. That's definitely, you know, the way that we see. And we have made significant progress on the overall in the last three quarters. And these kinds of wins and business transformation that has actually happened is what resulted in TCS getting the Raising Star GSA award for us. So I'm pretty happy to actually carry this little thing here. >> Is that what this is? >> Absolutely. So it means a lot because our customer in our kind of reinforcing the value, the TCS, along with AWS is bringing to the customer. >> So I wasn't going to say anything. I just assumed that you were a 2001 Space Odyssey fan and you just brought, you know, a version of the monolith with you. I wasn't sure. Congratulations. >> Thank you. That's a quite an achievement especially in the relatively short period of time. And especially with the constraints that have been placed upon all of us. Did they give you like a schwag bag with a bunch of, with, you know, like they do at the academy awards? Are you familiar with that. >> We had a great fun event on Monday afternoon. >> Fantastic. >> Yeah. >> Aditya, talk about, you're a consultancy, your organization is a consultancy. Talk about how you engage with the customers that you are helping to bridge the divide between what their business requirements are, and the technology that AWS is delivering. Because I think we all agree that everything we're seeing here from AWS is wonderful, but without an organization like yours, actual end users, actual customers, have a hard time driving benefits. So, how do you approach that? >> Gladly thank you, Dave, and thank you for theCUBE for having us here. And just borrowing from what Krishna talked about, the three layers of value creation, the cloud for IT, cloud for business and cloud for innovation. We see the journeys clients take, to start with how they look at IT modernization, and go all the way to business transformation, and look at ecosystem transformation as well. For example, we just heard about Western Union and we just came off of one with SWBC where they have completely modernized the payment systems on AWS and TCS has been the partner for transforming that for them. And that not only just means the technology layers, but also re imagining business processes in the cloud. Moving on from the financial side, if you look at the digital farming, for example, we have been working with some of the leading, the transmitter players in the healthcare industry and in the manufacturing space to look at helping farmers with AI. Right? And helping them look at how they can ensure better analytics and drone capabilities for digital farming. Drug trial development and acceleration for time to market has been a front and center for all of us in the last two years where I've been helping pharmacy organizations get better and will bring up drug trials and reach the end customers better with cloud. So there's various examples here. >> I want to poke on that a little bit. >> Aditya: Yeah. So when TCS is engaging a customer, say in farming versus pharma, how much of your interaction with them is specialized by industry vertical or specific area expertise versus the generic workings that are going to be supporting that effort in the background? What does that look like? Are you going in first with a pharma discussion, first with the farm discussion, as opposed to an overall discussion? >> It's a great point you mentioned Dave because that's the sort of essence of TCS. Because the way we look at it, we actually appeal to the industry specific. So our domain and contextual knowledge is very important to appeal to the customers and to the various stakeholders, no longer are the days where you talk about technology as a means to an end. We talk about how end customers can benefit in that context of what they're going through in that industry. And how can then technology be part of that strategy, right? So, hence, as you rightly said, domain and context first, followed by technology powering the outcome. >> Even though farm and pharma sound a lot alike. >> Right, I showed you the very difference. >> And they may share some things in common. Yes, very, very different. Krishna, talk about your go to market motion. How are clients aware of TCS? Do you have teams that engage clients directly and then bring AWS into the conversation? Or are you being brought in by AWS? Is it a combination? What does that look like? >> So, very good relevant question. So our GTM strategies is TCS has been in the, you know, serving the enterprise customers and IT transformation for 52 years now. So we have a huge base. But specifically from an AWS BU perspective, we are focusing on selective verticals, banking financial services and insurance is large, life sciences, health care, and travel, transportation and hospitality. So these are the verticals that we're actually focusing on, and given our presence in the enterprise sector, we already have a direct sales teams who are engaging with the customers directly on enterprise transformation and business transformation. And once we have that conversation, we actually take all these solutions that we have built on AWS and along with AWS. There are few customers in the last three quarters, after farming the AWS business unit, one thing that we did is with AWS we're proactively going and identifying the logos and the customers. And with the focus not on technology, with the focus on how to solve their problems on the business side and how to create new business models. So it's kind of both. We bring in, AWS brings in logos as well, so Greenfield accounts, and as well as our contextual knowledge of the industry is how the GTM is working out, and working out pretty good. >> You mentioned, you've been at this for 52 years. >> Aditya: Yeah. >> You must've been very young when you started doing this. Talk about the internal dynamics. So think of TCS, the larger organization. You represent the AWS business unit. TCS has been doing this for a long time, predating what we think now of as cloud. I'm sure that you have long existing relationships with customers, where you've been doing things for them that aren't cloudy, and those things keep the lights on at TCS, right? Important sources of revenue. Yet you're going in and you're consulting and saying, hey, you know, it might be better for you, Mr. Customer, to work with AWS and TCS, as opposed to maybe being at a data center that TCS manages, I mean, how do you manage that internal dynamic? You've got to have people at TCS who are saying, stay away, that's my revenue, don't move my cheese. What does that look like? >> Very valid question Dave. So the way that TCS is actually looking at is, twin engine strategy. There's a cost and optimization strategy, which we have. We sell the customers and operations, running the BAU if you will, business as usual, then you have something called growth and transformation. So as a strategy that we are very clear that the path of business transformation is growth and transformation channel. So we as a company are very comfortable cannibalizing our C and O in a business because we want to be relevant to the market, relevant to the customer, and relevant to the partner ecosystem. So the only way you are relevant is actually to challenge yourself, cannibalize your own business, and for the long, you know, strategy of looking at how to grow. And that's how our twin engine strategy is working. And there are a lot of customers where we have developer with contextual knowledge serving 20 years, 25 years of the customers. We know how they work, what their business is actually, you know, what's going to be the future of the business. So we are in a better position to actually transform them. And as a company, we already took cannibalize our revenue. >> So Adi, give us an example of working with a customer and give us an idea of what that customer's perspective is in terms of their place on the spectrum of, I don't want to move anything if I don't have to versus, hey, you guys can't move fast enough to deliver what I want. Where are you seeing that spectrum of customer requirements at this point? Do you feel like you're having to lead people to water still? Where are we with that? >> Well, if you asked me this question a couple of years ago, it would be about, hey, look, here's a beautiful water and the lake looks good, why don't we spend by the side and see what it tastes like? Now the question is, how much water to drink? Right? So the point being that customers have fast realized that cloud is not just an IT decision, it's a business transformation decision. So if I may just call it back what Krishna talked about, the dual engine strategy. A clear Testament to that is some of our relationships, most of our relationships are the matter has been over two decades with our clients. And that's a perfect indication of being constantly relevant for them because as their models change, as their markets change, customer expectations change, we need to constantly innovate ourselves. >> You're innovating your business just like that. >> Absolutely. >> Correct. >> So you know, as we say, you're in the boat with them and you're going through the same changes. >> And so coming back to the question which you asked, the point was we give them a point of what experience they can have with cloud by each stakeholder. The CIO wants to look at how we can look at better sustainability of their operations, keep the lights on as you said, enhance stability with more automatable capabilities, looking at DevOps, the business is completely looking at how can cloud fundamentally change my business model. And you have both these stakeholders coexisting with the same outcome towards enterprise transformation. And that's the experience which we work with them to shape. To say what the starting point is? Where would they like to go? And how can we go to them in the journey? What's interesting here is, nobody has all the answers. Neither is AWS nor customer the TCS, but we are here to create a culture of discovering the right goal and the right answers. It's very important. That's the approach to getting it working. >> Krishna and our last minute together. You've just received the Rising Star Award, 2022 is rapidly approaching, this doesn't put any pressure on you at all for 2022 because people are going to ask, what are those rising stars do again in 2022? What's on the horizon, what are the two of you excited about for next year? >> I think we are super excited with how AWS, you know, definitely in Adam's keynote, if I had to take a couple of points that I'm taking away is in addition to enhancing their core cloud capabilities, but if there's pivoted on industry solutions, you know, the fin space that they have announced, and the industrial solutions that they have announced. So that is where it very clearly aligns to our strategy of TCS, helping customers look for change their business models, implement new business models, create ecosystem play. And that's basically where we are really super excited. And another point which I took from Adam is the, they're focused on Edge with IOT and private 5G. And that's very, very important especially when you look at it both IT, as well as the IOT transformation. So we are super excited with the potential, all the new bells and whistles AWS is rolled out in last four days, And looking forward for few more of this. >> Congratulations again. It's a fantastic acknowledgement of what you've been able to do over the last, just three quarters as you mentioned, closing out 2021 in a very, very good way. Looking forward to 2022. Thank you gentlemen for joining us today here on theCUBE, and thank all of you for joining us, for continuing continuous Cube coverage of AWS re-Invent 2021. We are the leader in hybrid technology event coverage. I'm Dave Nicholson stay tuned for more from theCUBE.

>> Narrator: From around the globe, it's theCUBE, covering Fortinet Security Summit, brought to you by Fortinet. >> Welcome back to theCUBE, Lisa Martin here live in Napa Valley at the Fortinet Championship. This is the site of kickoff to the 2021-22 FedEx Cup regular series. We're here with Fortinet and we're here with one of our distinguished alumni, John Madison, the CMO and EVP of products. John, it's great to see you in person. >> Yes, Lisa it's been a while. >> It has been a while. >> Good to be back here, live. >> I know, you're not on Zoom, you're actually right six feet across from me. >> Yep, look, yes, it's definitely physical. >> It does, talk to me about the PGA and Fortinet. What are some of the synergies? >> There's a lot. I think one of the biggest ones is the culture of the two companies. So I mean, PGA tour, I think they've donated almost $3 billion to charities over the last 15 years, 20 years and we're the same. We would definitely want to give back to the community. We want to make sure we're providing training and education. We're trying to re-skill some of the veterans, for example, over 2000, also women in technology, you may have heard one of the key notes today about that, attempts from a education and training perspective. So there's a lot of synergies between the PGA Tour, and Fortinet from a cultural perspective. >> I love that. Cultural synergy is so important but also some of the initiatives, women in tech, STEM, STEAM, those are fantastic. Give our audience a little overview of what's going on here. We've got over 300 partners and customers here. What are some of the key themes being discussed today? >> Yeah, we're going to try and keep it smaller, this event. We don't want 10,000, 20,000 people. We'll keep it smaller. So about 300 customers and partners, and what we want to do is bring together, you know, the top people in cybersecurity and networking, we want to bring in customers so they can net with each other, we want to bring the partners here. And so, what you're going to see is you can see the tech expo behind you there, where people are talking technology. Some of the keynotes focus on areas like ransomware, for example, and cyber security in different industries. So definitely it's a smaller gathering, but I think it's very focused on cybersecurity and networking. >> Well, that's such an important topic these days. You know, you and I have spoken a number of times this summer by Zoom, and talking about the threat landscape and the changes-- >> Yep. >> And the work from anywhere. When you and I spoke, I think it was in June, you said 25% we expect are going to go back to the office, 25% permanently remote and the other 50 sort of transient. Do you still think given where we are now in September that that's still-- >> Yeah, I'm going to modify my prediction a bit, I think it's going to be hybrid for some time. And I don't think it's just at home or not at home or at work or not at work, I think it's going to be maybe one or two days, or maybe three days versus five days. And so, we definitely see the hybrid mode of about 50% for the next couple of years at least. I think that, you know, ransomware has been in the news a lot. You saw the Colonial, the ransomware has increased. We did a threat report recently. Showed about a 10X increase in ransomware. So, I think customers are very aware of the cybersecurity threats. The damage now is not just sucking information out and IP, it's causing damage to the infrastructure. So definitely the, you know, the attack surface is increased with people working from home, versus in the office, and then you've got the threat landscape, really, really focused on that ransomware piece. >> Yeah, ransomware becoming a household word, I'm pretty sure even my mom knows what that is. And talking about the nearly 11X increase in, what was that, the first half of 2021? >> Yeah, over the last 12 months. And I think what's also happened is ransomware used to be a broad attack. So let me send out, and see if I can find a thousand companies. Again, you saw with the Colonial attack, it's very targeted now as well. So you've got both targeted and broad ransomware campaigns going on. And a lot of companies are just rethinking their cybersecurity strategy to defend against that. And that work from home component is another attack surface. So a lot of companies that were operational technology companies that had air gaps and people would come to work, now that you can remotely get into the network, it's again, you can attack people at home, back into the network. >> Is that a direct correlation that you've saw in the last year, in terms of that increase in ransomware and this sudden shift to working from home? >> Well, I also think there's other components. And so, I think the ransomware organizations, the gangs, could use crypto more reasonably than checks and dollars and stuff like that. So they could get their money out. It became very profitable versus trying to sell credit card data on the dark web. So you saw that component. You also saw, as I said, the attack surface be larger for companies, and so those two things unfortunately have come together, and you know, really seen an exponential rise in attacks. >> Perfect storm. Let's talk about some of your customer conversations and how they've changed and evolved in the last 18 months. Give me a snapshot of when you're talking with customers, what are some of the things that they're coming to you for help, looking for the most guidance? >> Yeah, well I think, you know, the digital innovation transformation is almost accelerated because of, you know, COVID. They've accelerated those programs, especially in industries like retail, where it becomes almost essential now to have that digital connectivity. So they can't stop those programs. They need to accelerate those programs, but as they move those programs faster, again they expand their attack surface. And so, what I'm definitely seeing is a convergence of traditional kind of networking, connectivity, and cybersecurity teams like the CIO and the CSO working on projects jointly. So whether it be the WAN connectivity, or whether it be endpoint, or whether it be cloud, both teams are working much more closely going forward. >> Synergies there that are absolutely essential. Talk to me about what you guys announced with Linksys yesterday, speaking of work from home and how that has transformed every industry. Talk to us about the home work solution powered by Fortinet. >> Yeah, well, we definitely see work from home being there for some time. And so the question is, what do you do there? So I think initially 18 months ago, what happened was companies turned on their, what they call a VPN, which gives them an encrypted access when they went from 5% to a 100% people on the VPN. I speak to customers now and they're saying, that was kind of a temporary solution. It puts an end point security there. It was kind of temporary and now I need a longer-term solution because I can see this at least 50% for the next two years, being this hybrid work from home, and some of them are saying, "Well, let's look at something. Let's try and take the best of enterprise networking and security, and then try and match that with an easy to set up Wi-Fi or routing system." So the two companies, you know, have come together with this joint venture. We're taking Linksys technology from an ease of use at home, it's very simple to set up, you can do it on an app or whatever. And then we integrate the Fortinet technology inside there from a security and enterprise networking. The enterprises can manage themselves, the enterprise component and the consumer can manage their piece. What's very important is that separation as well. So the privacy of your home network, and then to make sure the enterprise piece is secure, and then also introducing some simple, what we call quality of service. So for a business person, things like Teams or Zoom as preference over some of the gaming and downloads of the family. So I think it brings the best of both worlds: ease of use and enterprise security together. >> I'm sure the kids won't like that it's not optimized for gaming, but it is optimized for things like video conferencing which, in the last year we've been dependent on for collaboration and communication. Tell me a little bit about the tuning for video conferencing and collaboration. >> Yeah, so we announced both Zoom and Microsoft Teams, probably the two biggest apps, which I use from a work from home business perspective. And definitely if you've got a normal system at home and your kids they've been downloading something, a new game or something like that, they can just take the whole bandwidth. And so the ability to kind of scale that back and make sure the Zoom meeting or the Teams meeting is first priority, I think is very important, to get that connectivity and that quality of service, but also have that security component as well. >> Yeah, the security component is increasingly important. Talk to me about why Linksys, was COVID the catalyst for this partnership? >> Well, I think we looked at it and we have our own work from home solutions as well. I mean, our own gear. We definitely wanted to find something where we could integrate into more of a ease of use solution set. And it just so happened we were speaking to Linksys on some other things and as soon as we started talking, it was very, very clear that this would be a great relationship and joint venture and so we made the investment. Not just "here's some of our code", we made a substantial investment in Linksys and yeah, we see some other things coming in the future as well. >> Can you talk to me a little bit about what the go to market will be, how can enterprises and consumers get this? >> Yeah. So it's more of an enterprise sale. I know some people think Linksys, they think consumer straight away. For us, this is a sale to the enterprises. So the enterprises buy it, it's a subscription service. So they just pay a monthly fee and they can have different levels of service inside there as well. They will get, you know, for each employee they'll get one, two or three nodes. And then so the, so the enterprise is paying for it, which I think will help a bit and they will manage it through their system, but the consumer will get this kind of a game that's very easy to use, very high speed connectivity, mesh technology. So yes, Linksys will sell some of it as well. But I think, you know, actually Fortinet will be the major kind of go to market because of our 500,000 business customers we have out there. >> Right. And your huge partner network. >> Yes. >> So let's talk about, give me a little bit of a view in terms of the benefit that IT will get leveraging the Linksys home work solution. I imagine that centralized visibility of all the devices connected to the corporate network, even though, wherever the devices are? >> Yeah, it actually extends the corporate network. So not in this initial release, in the second release. In the first release, they can go to a cloud portal and they can manage what they can manage from an enterprise perspective. The employee can go to the same portal, but gets a different view, can manage their piece. In the second release, we'll actually have support in our management systems. So if you're an existing Fortinet customer and you've got our management systems and say you've got, I don't know, 250 sites, and you're managing some of our firewalls or SD WAN systems, You'll be able to see all the employees links as systems as well, in that same management system. But again, there's a separation of duty and privacy where they can just manage the enterprise components, not they can't see the traffic from the employees' side, from the non-business transactions. >> Good. That privacy is key there. Do you think that in a perfect world, would help quiet down some of the perfect storm that we're seeing with ransomware and this explosion, this work from anywhere, work from home, going to be persisting technologies, like what you're doing with Linksys, is going to help make a dent in that spike? >> I think it's a component. So for us, the long term strategy for users, end point, this kind of Linksys component is an element. We also feel like there needs to be a transition of VPN technology into zero trust. So you're limiting again, the access to applications versus the network. And then definitely the third component would be a technology like EDR, which is more behavioral-based versus signature-based. And so you bring all those three together. Absolutely we'll make a dent in ransomware because you're just reducing the attack surface greatly, but also scanning the technology to make sure if you see something, you can act straight away. >> And then pair that with what you guys are doing and the investment that Fortinet's been making for a while in training and helping to fill that cybersecurity skills gap, which is growing year on year. >> Yeah. I speak to a lot of CSOs and CIOs and they go "What's the latest technology? What can you do next?" I say, well, the most important thing you can do is train your people. Train them not to click on that phishing link, right? Because still our numbers are around 6% of employees click on things and it doesn't matter what company you are. And so the education and the training is the one of the core, the most basic steps. We're introducing what we call an IT awareness program as part of NSC, which allows companies to download some tools. And they'll try some phishing emails that go out there, they'll see the response, see how they can (mumbles). So I always say that the people, the social engineering is the first step to try and fix and reduce. That's the biggest attack surface you will have. >> It's getting so sophisticated and so personalized. I mean I've seen examples with training that I've done for various companies where you really have to look 2, 3, 4 times at it and have the awareness alone to know that this might not be legitimate. >> Yeah, especially when people are just clicking on more things because they're going to more places. And so you have to be very careful. You can stop a bunch of that with some rule sets. So the systems, but if they're faking the domain, spear phishing, where they know exactly the context of where the email's coming out, it's hard, but you've just got to be very, very careful. If in doubt don't click on it. >> I agree if in doubt, don't click it. Well, John, it's always great talking to you. Exciting to hear the growth of Fortinet, what you're doing with PGA tour, the synergies there, the cultural synergies and the growth in customers and partners, lots of stuff to come. Can't wait till our next conversation, which I hope is also in person. >> Yes, yes, yes, for sure. You know, I think this is a great venue in that it's- as you can see it's open, which helps a lot. >> Yeah. >> It's not far from our headquarters, just down the road there, we've committed to this event for six or seven years. And so this is our first time, but definitely we're hoping to get out a bit more as we go forward. >> Excellent. I'm glad to see to see a company like Fortinet taking the lead and you look like you're dressed for golf. You said you have meetings, but I'm going to let you go because you probably have to get to that. >> I have a few more meetings. I wish they would leave a little gap for some golf. I'll try and work one as we go forward. >> Yeah. Anyway, John, thank you for joining me, great to see you. For John Madison, I'm Lisa Martin. You're watching theCUBE from the Fortinet Championship Security Summit in Napa. (Upbeat music)

>> Narrator: From around the globe, it's theCUBE with digital coverage of IBM Think 2021 brought to you by IBM. >> Well, hello everybody and welcome again to theCUBE. We continue our initiative here at IBM Think and now we're joined by two distinguished guests who are really going the extra mile for us, I might say. Here we are in the States at a very reasonable hour, in Korea, it's a little later in the evening so we certainly appreciate their time and their patience here. We're joined by Mr. Khee-Hong Song, who is the CEO and President of IBM Korea and Mr. Jung Sik Suh, who is the CEO of Hyundai AutoEver, which is an IT service company affiliated with the Hyundai Motor Group. And gentlemen (greeting in Korean) Thank you for joining this. We appreciate it. >> Thank you. >> Thank you for inviting us. >> Hi. >> Yes, hi, very good to see you there. And I hope I didn't do the greeting injustice there. First off, Khee, I'll start with you. Let's talk about first off, kind of this digital transformation that transpires not only here in the United States, but of course is global. And certainly, with an IT advanced company like Korea, give us just really kind of a calibration, where are you in terms of this transformation in Korea with regard to digital? >> A lot of people are interested in the post-COVID world and how it is going to look like. What changes this pandemic will bring. The Korean government is really focusing on growing the digital sector. Taking this advantage, and taking this opportunity as a chance to really upgrade the entire IT system of the nation. So for example, like a Korean economy had been contracted by -1% and industry players also faced difficulties. For example, discount stores are -20% Y2Y. department stores are lost 30% of their revenue. But the government is injecting money to really change the game, leveraging the digital technology. >> Yeah, and you mentioned COVID, and obviously that's had a global impact. Not only in your operations here in the United States certainly, but Africa in Europe, and certainly in Asia as we talked about. Can you go just a little bit deeper on that in terms of what those impacts have been and maybe a little more specificity on coming out of that. You mentioned the economic impacts that Korea is currently suffering, but looking for a bounce back, looking for a rebound with the government. Maybe a little more specifics about the impact of COVID. And then Mr. Sung, I'll turn to you for that as well. First off, Khee, if you will. >> Okay, in an effort to recover from COVID-19 economic recession, Korean government announced Digital New Deal, which is to lay a foundation for digital economy that will spur economic growth and innovation. Now the policy aims to create a new digital economy, which is underpinned by new technologies such as 5G, big data and artificial intelligence. According to IDC research, 55% of Korean companies have already overcome the economic downturn and are moving toward the growth in next normal. They have been very active in making investments to become the enterprise of the future. And this is higher than global average of 37% in terms of recovery rate. This indicates that leading Korean companies are quickly preparing for the next, even in the face of a crisis. >> Jung, We've been hearing from Khee talking about the digital and certainly the impacts of COVID. And I assume that at Hyundai, you have had to deal with this certainly, this impact and are now coming out the other end, some very positive news from numbers we're hearing from Khee. If you could talk about though, maybe from your perspective in terms of that impact. And then, what kind of a rebound do you see or kind of positive uptick do you see in terms of digital in your business, say, in the next 12 to 18 months? >> I think the 12 to 18 months, we are reinforcing the digitalization, not just the working environment, but also others, especially for in terms of sales. Until now most of the B2C sales changed to digital or the internet environment, but unfortunately, car manufacturing OEM companies are not too ready for the e-commerce environment. But Hyundai is very actively, and proactively, and preemptively starting the e-commerce. So I think, next to 12 to 18 month, two-digit percent of our sales are will be fulfilled by internet-based. I mean, we'll have to face the most biggest and most challenging but possible change after COVID. >> Yeah, what's driving that then, is it just that people are more likely to want to be at home whether it's as a consumer or whether it's your workforce, whatever the case may be, but you're talking about this kind of going from a physical world to a more digital-based world as I'm hearing you describe it. Is that accurate? >> Yes. So we are the digital world, from just communicate with customer, but also our internal operation. Like the manufacturing environment and also the sales environment, et cetera. >> And Khee, if you would talk about maybe how this is impacting your business and just in terms of IBM in general. Not just with Hyundai, but I'm sure you support a lot of healthcare initiatives, a lot of other e-commerce initiatives and what have you, What's kind of the bottom line impact there for you right now in terms of this massive shift over to digital? >> Well, in IBM, our goal is to work with industry clients and technology partners to accelerate this transformation through automation, transition to hybrid cloud, and help our clients to really gain some benefits from their change. So one area I can talk about is automation. We see increasing requirements from our clients on automation for operational excellence, amid the economic downturn, and for hygiene purposes as well. So Seoul Asan Hospital is one of the leading hospitals in Korea and has the largest number of beds. Asan hospital and IBM worked together to develop a bed allocation automation system based on design thinking, workshop and garage method. The automation system considers a patient's specific preferences, surgery schedule, customized treatment for each patient, and various reservation status in each department. The result was outstanding. The hospital could reduce the bed assignment lead time from 20 minutes to seven minutes with a 0% error rate. And currently, more than a hundred hospitalization registration procedures are being processed every day without human intervention. And patient satisfaction and productivity of medical staff have improved significantly. That is just one great example of automation which is taking place in many other industries as well. Second is transformation to cloud. A large credit card company in Korea has chosen IBM as a partner to convert enterprise wide systems including the most complex account system to a managed private cloud using cloud technology from IBM and Red Hat. >> Khee, you talked about these key factors, if you will, about cloud transformation and different kinds of operational efficiencies and all these very fundamental. But very important factors to consider, when you're talking to your clients right now, what are their, I wouldn't say hesitations, but I guess maybe their challenges in deciding what tasks will go where and to what degree they're good with the cloud environment, to what degree they want it still on prem, to what, where the hybrid comes into play. I mean, these are all are fairly crucial decisions that your clients are making. >> Well, I think the barrier to any decision, like quick decision or sort of complete understanding is the technology itself is changing very quickly. I mean, last year, two years ago, versus now, when all technology companies, should we say something different. And that is not because it changed the position itself. The technology itself changed, and technology companies are responding to the trend. So that's why some clients get confused, and that confusion slows down the adaption of digital technology. But as I mentioned earlier, this pandemic situation, I'm pretty sure they're, like Mr. Sung can talk about some changes in Hyundai motors. Many companies realized that doing nothing or slowing down is not the best answer in this environment. And they are now proactively embracing those changes. >> So Jung, if you would then follow up on that, I would like to hear from you about Hyundai and the factors that you've considered in your digital decision making in terms of workloads, and capacities, and just where you house information, where you house your data, where you process it. What are some of those factors that you have thought about and then maybe going forward, how much more are you going to do? What are you considering right now in terms of future transformations? >> I think the other, our competitor, the other OEMs also think like that the car itself should be changed to digital. It means that, currently, the software portion of the car is just a seven to 10% of total our, the procurement. But it'll be changed to 20 to 30% in five years. It means that some portion will be to increased by three times There is a one our research changed. The other one is that kind of a software mostly located and not just in the car, which means that car is just a software edge activity. It means that just that the input and output, or some real-time transaction, or other computation and calculation analysis and decision could be the car cloud. Therefore, the cloud is main party of the car software. And also the car is it's just to edge. We have edge cloud and main cloud. It will be occurred just to within just several years. First, really, Hyundai has currently more than 40% of the car is connected in listening. And also cumulatively, we are connected by around the four million car in the word. It will be changed to 10 million car would be connected within one years. >> So 10 million Hyundai cars will be connected to cloud generating information and also- >> Yes, collecting information. And we are ready for the OTA, which means over-the-air software update for the 10 million car within one years. And also, it will double up year by year. >> Okay. >> Which means that all of the car, all the operated by cloud. >> Okay. >> And cars, it says to input and output an edge activities, therefore car is on cloud. >> Okay. >> John: Right? Khee: Interesting. >> Jung: That is the major driver for our digital transformation. >> And if you would, just what role is IBM having that? You're talking about a massive increase of 10 million cars is a very impressive number. >> And the data, the 10 million cars are producing are will be enormous. So IBM's role is actually helping clients in this kind of situation. To help those companies collect data and then like a seamless communication with the cloud. So that at the real time, the 10 million cars get the information timely. And also, like all those cars are communicating with each other that is made possible upon a hybrid cloud platform. And I think that is IBM's contribution to Hyundai Motors. Not just Hyundai Motors, but industries who have similar challenges and desires. >> One more thing, lately, IBM helped us our all IT operation in US and Europe, which composed of our 50% of our revenue come from. Therefore it means that dozens of billion of revenue operation is located in US and Europe. All over the US, Europe IT operation conducted by the IBM India and orchestrated by IBM Korean people. >> So it's amazing as Mr. Suh mentioned, IBM Korea is leading the project. All the service delivery is done in India leveraging IBM India. And we are serving Hyundai motors in the United States and Europe. So it's a truly a global IT operation environment. And that is made possible based upon IBM's cloud technology. >> Well, your summary was spot on. I couldn't say it any better, Khee. Thank you for that. Jung, thank you as well. Talking about this impressive global impact and really partnership that Hyundai is taking with IBM in the several continents. And making it work for millions of consumers around the world. Thank you both for your time today. I appreciate it. >> Khee: Thank you very much, John. >> Jung: Thank you. >> All right, we've been talking about Korea as an IT power country for the IBM perspective. And certainly, using Hyundai is a beautiful example of just how this partnership is working and growing, and providing great service for consumers at the end of the day. You've been watching "theCube" and IBM Think. (upbeat theme music) (upbeat theme music) (humming)

(bright theme music) (humming) >> From around the globe, it's "theCUBE" with digital coverage of IBM Think 2021 brought to you by IBM. >> Well, hello everybody and welcome again to "theCUBE." We'll continue our initiative here at IBM Think and now we're joined by two distinguished guests who are really going the extra mile for us, I might say. Here we are in the States at a very reasonable hour, in Korea, it's a little later in the evening so we certainly appreciate their time and their patience here. We're joined by Mr. Ki-Hong Song, who is the CEO and President of IBM Korea and Mr. Jung Sik Suh, who is the CEO of Hyundai AutoEver, which is an IT service company affiliated with the Hyundai Motor Group. And gentlemen (speaking foreign language) Thank you for joining this. We appreciate it. >> Thank you. >> Thank you for inviting us. >> Hi. >> Yes, hi, very good to see you there. And I hope I didn't do the greeting injustice there. First off, Ki, I'll start with you. Let's talk about first off, kind of this digital transformation that transpires not only here in the United States, but of course is global. And certainly, with an IT advanced company like Korea, give us just really kind of a calibration, where are you in terms of this transformation in Korea with regard to digital? >> A lot of people are interested in the post-COVID world and how it is going to look like. What changes this pandemic will bring. The Korean government is really focusing on growing the digital sector. Taking this advantage, and taking this opportunity as a chance to really upgrade the entire IT system of the nation. So for example, like a Korean economy had been contracted by -1% and industry players also faced difficulties. For example, discount stores are -20% Y2Y. department stores are lost 30% of their revenue. But the government is injecting money to really change the game, leveraging the digital technology. >> Yeah, and you mentioned COVID, and obviously that's had a global impact. Not only in your operations here in the United States certainly, but Africa in Europe, and certainly in Asia as we talked about. Can you go just a little bit deeper on that in terms of what those impacts have been and maybe a little more specificity on coming out of that. You mentioned the economic impacts that Korea is currently suffering, but looking for a bounce back, looking for a rebound with the government. Maybe a little more specifics about the impact of COVID. And then Mr. Sung, I'll turn to you for that as well. First off, Ki, if you will. >> Okay, in an effort to recover from COVID-19 economic recession, Korean government announced Digital New Deal, which is to lay a foundation for digital economy that will spur economic growth and innovation. Now the policy aims to create a new digital economy, which is underpinned by new technologies such as 5G, big data and artificial intelligence. According to IDC research, 55% of Korean companies have already overcome the economic downturn and are moving toward the growth in next normal. They have been very active in making investments to become the enterprise of the future. And this is higher than global average of 37% in terms of recovery rate. This indicates that leading Korean companies are quickly preparing for the next, even in the face of a crisis. >> Jung, We've been hearing from Ki talking about the digital and certainly the impacts of COVID. And I assume that at Hyundai, you have had to deal with this certainly, this impact and are now coming out the other end, some very positive news from numbers we're hearing from Ki. If you could talk about though, maybe from your perspective in terms of that impact. And then, what kind of a rebound do you see or kind of positive uptick do you see in terms of digital in your business, say, in the next 12 to 18 months? >> I think in this 12 to 18 months, we are reinforce the digitalization, not just the working environment, but also others take this, especially for in terms of sales. Until now most of the B2C sales changed to digital or the internet environment, but unfortunately, car manufacturing OEM companies are not too ready for the e-commerce environment. But Hyundai is very actively, and proactively, and preemptively started the e-commerce. So I think, next to 12 to 18 month, two-digit percent of our sales are will be fulfilled by internet-based. I mean, we'll have to face the most biggest and most challenging but possible change after COVID. >> Yeah, what's driving that then, is it just that people are more likely to want to be at home whether it's as a consumer or whether it's your workforce, whatever the case may be, but you're talking about this kind of going from a physical world to a more digital-based world as I'm hearing you describe it. Is that accurate? >> Yes. So we are the digital world, from just communicate with customer, but also our internal operation. Like the manufacturing environment and also the sales environment, et cetera. >> And Ki, if you would talk about maybe how this is impacting your business and just in terms of IBM in general. Not just with Hyundai, but I'm sure you support a lot of healthcare initiatives, a lot of other e-commerce initiatives and what have you, What's kind of the bottom line impact there for you right now in terms of this massive shift over to digital? >> We'll, in IBM, our goal is to work with industry clients and technology partners to accelerate this transformation through automation, transition to hybrid cloud, and help our clients to really gain some benefits from their change. So one area I can talk about is automation. We see increasing requirements from our clients on automation for operational excellence, Meet the economic downturn, and for hygiene purposes as well. So Seoul Asan Hospital is one of the leading hospitals in Korea and has the largest number of beds. Asan hospital and IBM worked together to develop a better allocation automation system based on design thinking, workshop and garage method. The automation system considers a patient's specific preferences, surgery schedule, customized treatment for each patient, and various reservation status in each department. The result was outstanding. The hospital could reduce the bed assignment lead time from 20 minutes to seven minutes with a 0% error rate. And currently, more than hundred hospitalization registration procedures are being processed every day without human intervention. And patient satisfaction and productivity of medical staff have improved significantly. That is just one great example of automation which is taking place in many other industries as well. Second is transformation to cloud. A large credit card company in Korea has chosen IBM as a partner to convert enterprise wide systems including the most complex account system to a managed private cloud using cloud technology from IBM and Red Hat. >> Ki, you talked about these key factors, if you will, about cloud transformation and different kinds of operational efficiencies and all these very fundamental. But very important factors to consider, when you're talking to your clients right now, what are their, I wouldn't say hesitations, but I guess maybe their challenges in deciding what tasks will go where and to what degree they're good with the cloud environment, to what degree they want it still on prem, to what, where the hybrid comes into play. I mean, these are all are fairly crucial decisions that your clients are making. >> Well, I think the barrier to any decision, like quick decision or sort of complete understanding is the technology itself is changing very quickly. I mean, last year, two years ago, versus now, when all technology companies, should we say something different. And that is not because it changed the position itself. The technology itself changed, and technology companies are responding to the trend. So that's why some clients get confused, and that confusion slows down the adaption of digital technology. But as I mentioned earlier, this pandemic situation, I'm pretty sure they're, like Mr. Sung can talk about some changes in Hyundai motors. Many companies realized that doing nothing or slowing down is not the best answer in this environment. And they are now proactively embracing those changes. >> So Jung, if you would then follow up on that, I would like to hear from you about Hyundai and the factors that you've considered in your digital decision making in terms of workloads, and capacities, and just where you house information, where you house your data, where you process it. What are some of those factors that you have thought about and then maybe going forward, how much more are you going to do? What are you considering right now in terms of future transformations? >> I think the other, our competitor, the other OEMs also think like that the car itself should be changed to digital. It means that, currently, the software portion of the car is just a seven to 10% of total our, the procurement. But it'll be changed to 20 to 30% in five years. It means that some portion will be to increased by three times There is a one our research changed. The other one is that kind of a software mostly located and not just in the car, which means that car is just a software edge activity. It means that just that the input and output, or some real-time transaction, or other computation and calculation analysis and decision could be the car cloud. Therefore, the cloud is main party of the car software. And also the car is it's just to edge. We have edge cloud and main cloud. It will be occurred just to within just several years. First, really, Hyundai has currently more than 40% of the car is connected in listening. And also cumulatively, we are connected by around the four million car in the word. It will be changed to 10 million car would be connected within one years. >> So 10 million Hyundai cars will be connected to cloud generating information and also- >> Yes, collecting information. And we are ready for the OTA, which means over-the-air software update for the 10 million car within one years. And also, it will double up year by year. >> Okay. >> Which means that all of the car, all the operated by cloud. >> Okay. >> And cars, it says to input and output an edge activities, therefore car is on cloud. >> Okay. >> Right? >> Interesting. >> That is the major driver for our digital transformation. >> And if you would, just what role is IBM having that? You're talking about a massive increase of 10 million cars is a very impressive number. >> And the data, the 10 million cars are producing are will be enormous. So IBM's role is actually helping clients in this kind of situation. To help those companies collect data and then like a seamless communication with the cloud. So that at the real time, the 10 million cars get the information timely. And also, like all those cars are communicating with each other that is made possible upon a hybrid cloud platform. And I think that is IBM's contribution to Hyundai Motors. Not just Hyundai Motors, but industries who have similar challenges and desires. >> One more thing, lately, IBM helped us our all IT operation in US and Europe, which composed of our 50% of our revenue come from. Therefore it means that dozens of billion of revenue operation is located in US and Europe. All over the US, Europe IT operation conducted by the IBM India and orchestrated by IBM Korean people. >> So it's amazing as Mr. Suh mentioned, IBM Korea is leading the project. All the service delivery is done in India leveraging IBM India. And we are serving Hyundai motors in the United States and Europe. So it's a truly a global IT operation environment. And that is made possible based upon IBM's cloud technology. >> Well, your summary was spot on. I couldn't say it any better, Ki. Thank you for that. Jung, thank you as well. Talking about this impressive global impact and really partnership that Hyundai is taking with IBM in the several continents. And making it work for millions of consumers around the world. Thank you both for your time today. I appreciate it. >> Thank you very much, John. >> Thank you. >> All right, we've been talking about Korea as an IT power country for the IBM perspective. And certainly, using Hyundai is a beautiful example of just how this partnership is working and growing, and providing great service for consumers at the end of the day. You've been watching "theCube" and IBM Think. (upbeat theme music) (upbeat theme music) (humming)

(upbeat music) >> From around the globe, it's theCUBE! With digital coverage of IBM Think 2021 brought to you by IBM. >> Well, hello everybody. and welcome again to theCUBE. We continue our initiative here of IBM Think. and now we're joined by two distinguished guests who are really going the extra mile for us, I might say. Here we are in the States at a very reasonable hour, in Korea, it's a little later in the evening so we certainly appreciate their time and their patience here. We're joined by Mr. Kheehong Song, who is the CEO and president of IBM Korea and Mr. Jung-Sik Suh, who is the CEO of Hyundai AutoEver which is an IT service company affiliated with the Hyundai Motor Group. Gentlemen, (speaks in foreign language) thank you for joining us. We appreciate it. >> Thank you. >> Thank you, hi. >> Hi, it's very good to see you there. And I hope I didn't do the greeting injustice there. First off, Khee I'll start with you. Let's talk about first off, kind of this digital transformation that transpires not only here in the United States, but of course, is global. And certainly with an IT advanced company like Korea, give us just really kind of a calibration, where are you in terms of this transformation in Korea with regard to digital? >> A lot of people are interested in the post COVID world and how it is going to look like, what changes this pandemic will bring. The Korean government is really focusing on growing the digital sector, taking this advantage. And taking this opportunity here as a chance to really upgrade the entire IT system of the nation. So for example, like a Korean economy had been contracted by negative 1%, and industry players also faced difficulties. For example, discount stores, negative 20% Y2Y department stores lost 30% of their revenue, but the government is injecting money to really change the game, leveraging the digital technology. >> Yeah, and you mentioned COVID. And obviously that's had a global impact, you know, not only in your operations here in the United States, certainly, but Africa, in Europe and certainly in Asia as we talked about. Can you go just a little bit deeper on that in terms of what those impacts have been, and maybe a little more specificity on coming out of that? You mentioned the economic impacts that Korea is currently suffering, but looking for a bounce back, looking for a rebound with the government, maybe a little more specifics about the impact of COVID. And then Mr. Song, I'm going to turn to you for that as well. First off, Khee, if you would. >> Okay. In an effort to recover from COVID-19 economic recession, Korean government announced digital new deal which is to lay a foundation for a digital economy that will spur economic growth and innovation. Now, the policy aims to create a new digital economy which is underpinned by new technologies, such as 5G, big data and artificial intelligence. According to IDC research, 55% of Korean companies have already overcome the economic downturn and are moving toward across the next normal. They have been very active in making investments to become the enterprise of the future. And this is higher than global average of 37%, in terms of recovery rate. This indicates that leading Korean companies are quickly preparing for the next even in the face of a crisis. >> Jung, we've been hearing from Khee talking about the digital and certainly the impacts of COVID. And I've assumed that at Hyundai, you know, you have had to deal with this, certainly this impact, and are not coming out the other end some very positive news from numbers we're hearing from Khee. If you could talk about though, maybe what from your perspective, in terms of that impact and then what kind of a rebound do you see, or kind of positive uptake do you see in terms of digital and your business say in the next 12 to 18 months? >> I think the next 12 to 18 months, the reinforcers of digitalization, not just the working environment, but also other respect especially for the... in terms of sales. You know, until now, most of the B2C Series changed to digital or the internet environment, but unfortunately, car manufacturing OEM companies aren't ready for the E-commerce environment. But Hyundai is very actively and proactively, and preemptively started at E-commerce. So I think next 12 to 18 month, two digit percent of our sales, I mean fulfilled by internet (mumbles), I mean the objective is the most biggest and most challenging, but possible changing after COVID. >> Yeah, what's driving that and then, it's just that people are more likely to want to be at home whether it's as a consumer or whether it's your workforce whatever the case may be, but you're talking about this kind of going from a physical world to a more digital-based world, as I'm hearing you describe that, is that accurate? >> Yes. So we are, the digital world, from just communicate with the customer, but also the, our internal operation, you know, like the manufacturing environment, and also the sales environment, et cetera. >> And Khee, if you would talk about maybe how this is impacting your business and just in terms of IBM in general, not just with Hyundai, but I'm sure you support a lot of healthcare initiatives, a lot of other E-commerce initiatives and what have you. What's kind of the bottom line impact there for you right now, in terms of this massive shift over to digital? >> In IBM, our goal is to work with industry clients and technology partners to accelerate these trends maybe mention through automation, transition to hybrid cloud and help our clients to really gain some benefits from their change. So one area I can talk about is automation. We see increasing requirements from our clients on automation for operational excellence, meet the economic downturn, and for hygiene purposes as well. So Seoul Asan hospital is one of the leading hospitals in Korea and has the largest number of beds. Asan hospital and IBM worked together to develop a bed location automation system, based on design thinking workshop and garage method. The automation system considers our patient's specific preferences, surgery schedule, customized treatment for each patient, and various reservation status in each department. The result was outstanding. The hospital could reduce the bed assignment lead time from 20 minutes to seven minute with a 0% error rate. And currently more than a hundred hospitalization registration procedures are being processed every day without human intervention. And patient satisfaction and productivity of medical staff have improved significantly. That is just one great example of automation which is taking place in many other industries as well. Second is a transformation to cloud. A large credit card company in Korea has chosen IBM as a partner to convert enterprise wide systems including the most complex account system to manage it private cloud using cloud technology from IBM and Red Hat. >> Khee, you talk about these key factors, if you will, about cloud transformation and different kinds of operational efficiencies, and all these you very fundamental but very important factors to consider. When you're talking to your clients right now, what are their I wouldn't say hesitations, but I guess maybe their challenges in deciding what tasks will go where, and to what degree they're good with the cloud environment, to what degree they want it still on prem, to what where the hybrid comes into play. I mean, these are all are fairly crucial decisions that your clients are making. >> I think the barrier to any decision, like a quick decision or sort of complete understanding is the technology itself is changing very quickly. I mean last year, two years ago versus now when all technology companies should say something different. And that is not because they changed the position. Itself, the technology itself changed and technology companies are responding to that trend. So that's why some clients get confused, and that confusion slows down the adoption of digital technology. But as I mentioned earlier, this pandemic situation, I'm pretty sure they're like Mr. Suh can talk about some changes in Hyundai motors. Many companies realize that doing nothing or slowing down is not the best answer in this environment. And they are now proactively embracing those changes. >> So Jun, if you would then follow up on that, I would like to hear from you about Hyundai, and the factors that you've considered in your digital decision-making, in terms of workloads and capacities, and you know, just where you house information, where you house your data, where you process it. What are some of those factors that you have thought about and then maybe going forward how much more are you going to do? What else do, what are you considering right now in terms of future transformations? >> I think the other well, competitor the other OEMs also think like that, the, you know, the car itself should be changed to digital. It means that, you know currently the software portion of the car is just seven to 10% of total our, the procurement, but it'll be change it to 20 to 30% in near to five years. It means that software portion will be increased by three times. That is one our, that is to change it. The other one is that kind of a software mostly located not just in the car, which means that car is just a software engine activity. It means that just that the input and output, or some real time trajection. All other computation and calculation analysis and decision could be the car cloud. Therefore, the cloud is main body of the car software. And also just car it's just to edge. We have edge cloud and main cloud. It will be occurred just within several years. Because first of all, firstly, Hyundai has currently more than 40% of the car is connected in listening. And also cumulatively, we are connected by around four million car in the world. It will be change to 10 million, car would be connected within one years. >> So 10 million Hyundai cars will be connected to cloud generating information? >> Yes, collecting information, and we are ready for the OTA, which means that all over the air, software update for the 10 million car within one years. And also it will be double up, double up, double, year by year. >> Okay. >> Which means that all of the car will be operated by cloud. >> Okay. >> And car is test to input and output, and activities. Therefore car is on cloud. >> Okay. >> Right? >> Interesting. >> That is the major driver for our district transformation. >> And if you would just, what role is IBM have in that? You're talking about a massive increase of 10 million cars is a very impressive number. >> And the data, the 10 million cars are producing will be enormous. So IBM's role is actually helping clients in this kind of situation. To help those companies collect data and then like a seamless communication with the cloud. So they're like at the real time, the 10 million cars get the information timely, and also like all those cars are communicating with each other, that is made possible upon a hybrid cloud platform. And I think that is IBM's contribution to Hyundai Motors, not just Hyundai Motors, but industries who have similar challenges and desires. >> One more thing, already, IBM helped us, our IT operation in US and Europe, which composed of our 50% of our revenue come from. Therefore it means that (mumbles) billion revenue operation is located in US and Europe. All over the US, Europe, IT operation conducted by the IBM India. And orchestrated by IBM Korean people. >> So it's amazing as Mr. Suh mentioned like IBM Korea is leading the project. All the service delivery is done in India, leveraging IBM India. And we are serving Hyundai Motors in the United States and Europe. So it's truly a global IT operation environment, and that is made possible based upon IBM's cloud technology. >> Well, your summary was spot on. I couldn't say that any better. Khee, thank you for that. Jun, thank you as well, talking about this impressive global impact and really partnership that Hyundai is taking with IBM and the several continents. And making it work for millions of consumers around the world. Thank you both for your time today. I appreciate it. >> Thank you. >> Thank you very much, John. >> Thank you. >> All right, we've been talking about Korea as an IT powered country for the IBM perspective. And certainly using Hyundai is a beautiful example of just how this partnership is working and growing and providing great service for consumers, at the end of the day. You've been watching theCUBE and IBM Think. (upbeat music)

>>Yeah. Now I think we can all agree how valuable it is to hear from practitioners, and I want to thank the panel for sharing their knowledge with the community. One common challenge that I heard you all talk about was bringing your leadership and your teams along on the journey with you. We talk about this all the time and it is critical to have support from the top. Why? Because it directs the middle and then it enables bottoms up innovation effects from the cultural transformation that you guys all talked about. It seems like another common theme we heard is that you all prioritized data based decision making in your organizations, and you combine two of your most valuable assets to do that and create leverage employees on the front lines. And, of course, the data. There's rightly pointed out, Tom, the pandemic has accelerated the need for really leaning into this. You know the old saying, If it ain't broke, don't fix it, Will Cove. It is broken everything and and it's great to hear from our experts, you know how to move forward. So let's get right into it. So, Gustavo, let's start with you If I'm an aspiring change agent and let's say I'm a budding data leader, what do I need to start doing? What habits do I need to create for long lasting success? >>I think curiosity is very important. You need to be like I said in to what is happening not only in your specific feel, like I have a passion for analytics. I didn't do this for 50 years, Plus, but I think you need to understand well being other areas across not only a specific business, Aziz. You know, I come from, you know, Sam's Club. WalMart retail having energy management technology. So you have to try to put yourself and basically, what of your comfort, son? I mean, if you are staying in your comfort zone and you want to use one continuous improvement, that's just gonna take you. So far, what you have to do is, and that's what I try to do is I try to go into areas, businesses and transformations that make me, you know, stretch and develop a solider. That's what I'm looking to do so I can help transform the functions organizations and do the change management. The change of mindset is required for this kind of effort. >>Thank you for that. That is inspiring. And and Cindy, you love data, and the data is pretty clear that diversity is is a good business. But I wonder if you can you add your perspectives to this conversation? >>Yeah. So Michelle has a new fan here because she has found her voice. I'm still working on finding mine, and it's interesting because I was raised by my dad, a single dad. So he did teach me how toe work in a predominantly male environment. But why? I think diversity matters more now than ever before. And this is by gender, by race by age, by just different ways of working and thinking is because, as we automate things with a I, if we do not have diverse teams looking at the data and the models and how they're applied, we risk having bias at scale. So this is why I think I don't care what type of minority you are. Finding your voice, having a seat at the table and just believing in the impact of your work has never been more important. And and, as Michelle said, more possible >>great perspectives Thank you, Tom. I wanna go to you. I mean, I feel like everybody in our business is in some way, shape or form become a covert expert. But what's been the impact of the pandemic on your organization's digital transformation plant? >>We've seen a massive growth, actually, you know, in a digital business over the last 12 months, really even acceleration, right? Once, once covert hit, we really saw that, uh, that in the 200 countries and territories that we operate in today and service our customers and today that there has been a huge need, Right? Thio send money to support family, to support friends right and support loved ones across the world. And as part of that, you know, we were We are very honored to be to support those customers that we across all of Tucker's today. But it's part of the acceleration. We need to make sure that we had the right architecture and the right platforms to basically scale right to basically support and revive that kind of security for our customers going forward. So it's part of that way did do some some of pivots, and we did a accelerate some of our plans on digital help support that overall growth coming in and to support our customers going forward. Because during these times during this pandemic, right, this is the most important time we need to support those those that we love and those that we care about. And in doing that, some of those ways is actually, by sending money to them, support them financially. And that's where really, our products, our services, come into play that, you know, it really support those families. So it was really a great opportunity for us to really support and really bring some of our products to the next level and supporting our business going forward. >>Awesome. Thank you. Now I want to come back to Gustavo. Tom, I'd love you to chime in two. Did you guys ever think like you You were pushing the envelope too much and doing things with data or the technology that was just maybe too bold. Maybe you felt like at some point it was It was failing, or you're pushing your people too hard. Can you share that experience and how you got through it? >>Yeah, The way I look at it is, you know, again whenever I goto organization, I asked the question Hey, how fast you would like to transform and, you know, based on the agreements on the leadership and the vision that wanna take place, I take decisions and I collaborate in a specific way. Now, in the case of covet, for example, right, it forces us to remove silos and collaborate in a faster way. So to me, it was an opportunity to actually integrate with other areas and dr decisions faster. But make no mistake about it when you are doing a transformation, you are obviously trying to do things faster than sometimes people are comfortable doing. And you need to be okay with that. Sometimes you need to be okay with tension or you need to be okay. You know the betting points or making repetitive business cases until people connect with the decision because you understand. And you are seeing that Hey, the CEO is making a 12 year, you know, efficiency go. The only way for us to really do more with less is for us to continue this path. We cannot just stay with this type of school. We need to find a way to accelerate the transformation. That's the >>way. How about you talk? We were talking earlier with sedition, Cindy, about that bungee jumping moment. Do you? What could you share? >>Yeah, you know, I think you hit upon it. Uh, right now, the pace of change. When were the slowest pace that you see for the rest of your career? So as part of that right, that's what I tell my team is is that you need to be You need to feel comfortable being uncomfortable. I mean, that we get to be able to basically, uh, scale I expand and support that the ever changing needs the marketplace and industry and customers today in that pace of change that's happening, right? And what customers are asking for and the competition the marketplace, that's only going to accelerate. So as part of that, you know, as you look at what? How you're operating today in your current business model, right? Things are only going to get faster. So you have to plan into a line and to drive the actual transformation you so you can scale even faster in the future. So as part of that what we're putting in place here right is how do we create that underlying framework and foundation that allows the organization to basically continue to scale and evolve into the future? >>We're definitely out of our comfort zones, but we're getting comfortable with it. Cindy. Last question. You've worked with hundreds of organizations, and I got to believe that, you know, some of the advice I gave when you were at Gartner, which was pre co vid. You know, maybe sometimes clients didn't always act on it. You know, they're not on my watch for whatever variety of reasons, but it's being forced on them now. But knowing what you know, now that you know, we're all in this isolation economy, how would you say that? Advice has changed? Has it changed? What? What's your number one action and recommendation today? >>Yeah, well, first off, Tom just freaked me out. What do you mean? This is the slowest ever. Even six months ago, I was saying the pace of change in Data Analytics is frenetic. So But I think you're right, Tom. The business and the technology together is forcing this change. Now, Dave, to answer your question, I would say the one bit of advice. Maybe I was a little more very aware of the power and politics and how to bring people along in a way that they are comfortable. And now I think it's you know what? You can't get comfortable. In fact, we know that the organizations that were already in the cloud have been able Thio respond and pivot faster. So if you really want to survive, Aziz, Tom and Gustavo said, get used to being uncomfortable. The power and politics are gonna happen. Break the rules, get used to that and be bold. Do not do not be afraid to tell somebody they're wrong and they're not moving fast enough. I do think you have to do that with empathy. As Michelle said, and Gustavo, I think that's one of the key words today besides the bungee jumping. So I want to know where skiddish gonna go. Bungee >>jumping guys, Fantastic discussion, really, Thanks again, toe all the Panelists and the guests. It was really a pleasure speaking with you today, really, virtually all of the leaders that I've spoken to in the Cube program recently they tell me that the pandemic is accelerating so many things, whether it's new ways to work. We heard about new security models and obviously the need for cloud. I mean all of these things. Air driving, true enterprise wide digital transformation, not just a ZAY said before lip service. Sometimes we minimize the importance and the challenge of building culture and making this transformation possible. But when it's done right, the right culture is going to deliver tremendous, tremendous results. What does that mean? Getting it right? Everybody's trying to get it right. My biggest take away today is it means making data part of the DNA of your organization. And that means making it accessible to the people in your organization that are empowered to make decisions. Decisions that can drive you revenue could cost speed access to critical care. Whatever the mission is of your organization, data can create insights and informed decisions that Dr Value Okay, let's bring back side dish and wrap things up, so please bring us home. >>Thank you. Thank you, Dave. Thank you. The Cube team and thanks. Thanks. Goes toe all of our customers and partners who joined us. And thanks to all of you for spending the time with us, I want to do three quick things and then close it off. The first thing is, I want to summarize the key takeaways that I had from all four or four distinguished speakers. First Michelle, I was simply put it. She said it really well, that is be brave. And Dr Don't go for a drive along that it's such an important point. Often times you know the right thing that you have to do to make the positive change that you want to see happen. But you wait for someone else to do it, not just why not you? Why don't you be the one making That change happened? That's the thing that I picked Picked, picked up from Michelle's, uh, talk. Cindy talked about finding the importance of finding your voice, taking that chair, whether it's available or not, and making sure that your ideas your voices are heard, and if it requires some force and apply that force, make sure your ideas support. Gustavo talked about the importance of building consensus not going at things all alone, sometimes building the importance of building the core. Um, and that is critical because if you want the changes to last, you want to make sure that the organization is fully behind it. Tom, instead of a single take away. What I was inspired by is the fact that a company that 170 years old, 170 years old, 200 companies and 200 countries they're operating in, and they were able to make the change that is necessary through this difficult time. So in a matter of months, if they could do it, anyone could. The second thing I want to do is to leave you with a take away. That is, I would like you to go thought spot dot com slash NFL because our team has made an app for NFL on Snowflake. I think you will find this interesting now that you're inspired and excited because off Michelle stock and the last thing is please go to thought spot dot com slash beyond Our global user conference is happening in this December. We would loud toe have you join us. It's again virtual. You can join from any where we're expecting anywhere from 5 to 10,000 people. I would allowed to have you join Aunt uh see what we were up to since last year way have a lot of amazing things in store for you, our customers, our partners, our collaborators. They will be coming and sharing. You'll be sharing things that you've been working to release something that will come out next year. And also some of the crazy ideas of engineers have been hooking up. All of those things will be available for you at Fort Spot beyond. Thank you. Thank you so much.

>> live from Las Vegas. It's the queue covering del Technologies World twenty nineteen. Brought to you by Del Technologies and its ecosystem partners >> Hello and welcome to Day three Live coverage of the Cube here in Las Vegas Fridel Technologies World twenty nineteen I'm jut forward, David Lot They Davis del Technologies world. This is our tenth year If you count DMC World twenty ten first ever Cube event where we go out to the events and extract the signal from the noise. Now we're the number one and tech coverage. Howard Elias has been with us the entire way. Our next guest. Keep alumni Howard allies who is currently the President of Services and Digital for Del Technologies. Howard, great to see you. >> Great to see you, John. Dave. Always great to be back with you. Thank you. >> You've been with us throughout our entire cube jury. It's our tenth year has been great ride and one of the benefits of doing the queue besides learning a lot and having great conversations is as the industry of balls from true private private cloud to, you know, big day that meets technology, all the different iterations of the business. We're gonna have the conversation and look back and see who's right. You >> get to go back and see what we said and holds you >> accountable. Not that you guys said anything crazy, but you were unique because we've had many conversations and most notably during the acquisition of the M. C. You're on the team leading the effort with your partner in crime from the del side to make sure the acquisition goes smoothly. And, you know, a lot of people were saying, Oh my God, icebergs ahead. We're pretty positive. So history treats us fairly in the queue way. Tend to got it right. But you said some bold things. That was pretty much the guiding principle of the acquisition, and I just I just tweeted it out this morning. So you got it right. You said some things. Looking back two years later, almost two, three years later. >> Well, look, you know John first, I appreciate that. Appreciate the opportunity to be back with with you, and it's amazing. It's been ten years, but yeah, so, you know, over the last couple of years, I did help Kohli the integration, and we said, Look, first and foremost, we're going to do no harm the way customers transact with us byproducts. The way we service them, that's not going to change. But then, that's not enough, right? It's not just about doing no harm. It's how do we add value? Over time, we talked about aligning our teams in front of our customers. Then we talked about unifying the approach not just in the go to market, but in services and in technology and ultimately delivering Mohr integrated solutions. And we've accepted here down that a CZ you rightly say so thank you for pointing that out. And you know, this week was a great embodiment of that. Because not only are we listening, Tio, what our customers want we're delivering on it were actually delivering these integrated solutions the Del Technologies Cloud unified workspace for client, these air things that we've delivered over time, you know, we stitch it together, and now we're unifying it, integrating it, actually now even embedding services into it. So that's the journey we've been on. And we've been very pleased with the reception, >> and Michael to also was very bull. But the key on all the conversations we had on this was and we'LL get to the current situation now because that's important is that you guys saw the growth opportunities on the synergies we did, and we kind of had those conversations. So a line you align the team's unify and integrate you're the integration phase. Now we're starting to see some of the fruit come off the tree with business performance significant. Well, we appreciate >> that we're gaining market share across the board, and we had a hypothesis with, you know, coming together. We had a complementary product, portfolios, complimentary customer segments way. We're very thoughtful and how we organized our go to market, and we're seeing that we're seeing that and market share games. But more importantly, we're seeing the customer conversation saying Thank you for that. Now I want more. How do you deliver more value faster? So I think we're past the integration stays. Now we're into the accelerating the value stage. >> Howard, you've been through and seen a lot of acquisitions, large acquisitions. I mean, I think of the compact digital, you know, not a lot of not a lot of overlap. HP with compact, much more overlap maybe didn't go so as well. Or maybe a smoothly massive acquisition here. Why do you think it worked so well here? Because there was a failure. A fair amount of overlap, you know, definitely some shared values, but maybe some different cultures. You've been on both sides. It's just seems to be working quite well. You seem to be through that knothole of maybe some of that uncomfortable early days. Why do you think it works so well? What was kind of the secret sauce there? >> I think a couple of reasons. First, the hypothesis of coming together was all very customer centric. Customers wanted fewer more strategic partners. They ultimately from infrastructure, want Mohr integration. Mohr automation. They wanted a CZ. Pat said yesterday on states they wantto look upto absent data and somebody else worry about looking down and taking care of the infrastructure. So the hypothesis was very strong. Michael had a bold vision, but the boldness of actually execute on that vision as well, I would say second we have. Yeah, while the cultures, in terms of how things got done were a bit different, the values were frankly not just similar. They were identical. We may have talked about this before, but When we did the integration planning, we actually surveyed half the population of about Delanie emcee. The top five values in order were the same from both team members. Focus on customers Act with integrity. Collaborate When is a team results? Orientation? It was phenomenal. I would say. You know, third, it's just the moment in time. Uh, and it's really a continuation. You think about the ten year partnership that Dell and GMC had back in the two thousands that actually helped us get to know each other, how we worked and helped form those shared values. So and then, finally, approximate one hundred fifty thousand team members signed up to the mission. You know, the tech industry is starved for star for tech talent. On the fact of the matter would that we have approximately one hundred fifty thousand team members of prostate all technologies signed up to our vision, signed upto our strategy, executing every day on behalf of customers. It's just awesome to see >> So digital transformation, of course, is the big buzz word. So we're gonna put on you guys what do you do it for your own digital transformation? You know, proof of the pudding. What gives you the right to even talk about that? What do you doing? Internal? >> Yeah, you know, it's a great question. And to your point, we talked with customers all the time. In addition to looking after our services businesses worldwide, I also am responsible for Del Digital inside of Del Technologies. That's our organization. We purposely named Adele Digital because we are on our digital journey as well. And so we are transforming everything that we do the way we do. We actually call it the Del Digital Way. We've had a couple of nice breakouts. Our booth in the showcase has got Ted talk style conversations around this, and it's really embracing this notion of agile, balanced team's getting close to the business, actually, the business in the dojo, with our developers moving more to a product orientation versus a project orientation, and it's really focused on outcomes on T. You hear us talk about this all the time. Technology strategy is now business strategy, and whether it's in sales or marketing or services. Doug's doing great work and support assist using telemetry and artificial intelligence and machine learning recommendation engines in our dotcom. The on boarding within hours. Now with what we used to take weeks with our business customers in our premier portal, Wei are looking at every opportunity everything from the introduction of bots and our p a all the way through machine learning. Aye aye and true digital transformation. We are walking that talk. >> Really? You're going hard after our p A. That's what Do Yu result. We've >> actually been doing arpa for many, many years and for you know, especially when you have a complex system complex ecosystem As you're rewriting and developing either re platform, every factoring or cloud native, you still got to get work done. So I'll give you a great example. You know, in a online world of today, it's amazing to know that we still get millions of orders by email and facts. And instead of outsourcing that and having humans retyped the order, we just have robotics, read it automatically translated. And >> so the narrative in the media you hear a lot of coordination is going to kill jobs. But I've talked to several our customers and they've all said the opposite. We love this because it's replacing mundane tasks it allows us to do other things. What's your experience you are >> spot on? I'm a technology optimist, and I believe that a machine learning robotics will do the task that humans are either not good at or don't want to do or don't like to do and allow humans to be more human. Creative thinking, creative problem solving, human empathy, human compassion. That's what humans are good at. And we need more people focused on those things and not row test. >> One of the things that Michael Dell on key themes in The Kino Day one and Day two in some day. Three lot of societal impacts of I Love That's kind of touchy feely. But the reality is of Reese killing people. The skills gap is still a huge thing. Culture in the Enterprise is moving to a cloud operation was his favors your strategy of end to end consistent operational excellence as well as you know, data driven, you know, value of the AP player. Great straight, but we've been seeing in the queue with same thing for years. Horizontally, scaleable, vertically specialized in all industries. Yeah, with data center so good. Good strategy, gaps in culture and skills are coming up How are you guys doing services? You mean you've got a lot of people on them on the streets? A lot of people that need to learn more about a I dashboards taking the automation, flipping a new opportunity to create a value for people in the workplace. We >> have this conversation continuously inside of our teams and inside of our company. Look, we have a responsibility to make sure that we bring everybody along this journey. It starts by painting the vision being that technology optimist. Technology is a force for good on how do we apply the technology and the digitization and, you know, creating our digital future, bringing our team members along. So setting that vision, it is about culture behavior. Set the tone from the top. But we also have a responsibility and retraining and re skilling and bringing you know, team members. New opportunities, new ways to learn our education services team, for example. You see it here, the certifications, the accreditations. We do the hands on labs that we do. It's all about allowing opportunities for people to up skill, learn new skills, learn new opportunities that are available, and customers need this higher value. Helping support? What >> about the transformation that's been impacting the workflow on work streams of your services group with customers as they are? Maybe not as far ahead as you guys are on the transformation. Maybe they're They're cloud native in one area kind of legacy in the other. How was the impact of delivering services? One. Constructing them services, formulating the right products and service mix to delivering the value. How is technology change that you mentioned Rp? What if some of the highlights in your mind >> Well, it's It's a journey and you know it. Mileage varies here, right? Depends on what you're trying to accomplish, but we never do wrong by focusing on what's right for the customers. So what our customers looking for? What are their business outcomes they're looking for? Uh, here's a great example in the unified workspace. You know, we've been doing PC has a service for a while even before PC has a service. We're delivering outcomes, delivering Peces, doing some factory into get gration Cem image management, lifecycle management deployment services. But now what we've done is really taken not just the end and view, but we packaged it and integrated it into a single solution offering across the life cycles. So now, once we understand the the customer and users personas weaken factory, image the configuration, ship it to the team members deaths not just to a doctor the place but right to the team members desk have auto deployment auto support telemetry back and manage that life cycle, we package that up now. End to end this a new capability that customers are really looking for >> before I know. Do you have a question? I want to get your reaction to a quote I'm reading from an analyst. Bigtime firm New Solutions launched at Del. World Show that worked to align seven businesses for the last eighteen months is starting to pay off. We just talked about that. Cross Family Solutions minimizes time on configurations and maintenance, which opens up incremental, total addressable market and reduces complexity. Michael Dell yesterday said that there's a huge swath of market opportunity revenue wise in kind of these white space gap areas that were servicing, whether its image on PCs and you kind of mentioned peces of service analysts. E this is tam expansion, your common reaction. >> I couldn't say it better myself and look. The to integrate solutions we announced this week is a great example of that of the seams. It's workspace won its security from SecureWorks. It's the you know, del Endpoint management capabilities. It's the PC hardware itself. It's the services life cycle from Pro support Pro Deploy Pro Manage, all integrated in the end and easily Mohr consumable were even Do any are consulting business with our new pro consult advisory offer offer. But look at the Del Technologies Cloud del Technology infrastructure. With VM wear we'LL be adding PC after as a service. On top of that, this is exactly what customers >> So what's your marching orders to the team? Take that hill. Is it a new hills? The same hill? What's the marching orders down to the >> teaching orders is Get out and visit customers every single day. Make sure we understand how our technology and services are being utilized, consumed and impacted. And where do we add more value over time? >> So I wantto askyou for from a customer standpoint, we were talking about digital transformation earlier, and, you know the customer's always right is the bromide. You guys are very customer focused However, when it comes to digital, a lot of customers is somewhat complacent about obviously technology companies like yours embrace digital transformation. But I hear from a lot of companies. Well, we're doing really well. You know, I'm gonna be long gone, but before this really disrupts my industry, it's somewhat of a concern. Now, do you see that? And and how do you I mean, I think one of the reasons just so successful in your careers you take on hard problems and you don't freak out about it. You just have a nice even keel. What do you do when Because you reached you encounter that complex, Eddie, do you coach them through it? You just say okay. Customer's always right. But there's a concern that they'LL get disrupted in there. Your customer, they're spending money with you today. So how do you get through breakthrough? That complacence >> adds a great question and you know, one of the other marching orders I give tow my team is that things were going so well is time to change. And so this is what we have to take to our customers as well. And, uh, look, way have to be respectful about it. But we also have to be true telling, and so we will meet with our customers, hear them out and where they're doing well, well pointed up. But where they're not or where we've got different examples, we'LL just lead by example our own internal example, other customer examples in a very respectful way, but in a very direct way, especially at the senior levels where that's what they need to hear sometimes. >> So you have a question, because I got I wantto sort of switch topics like >> one of us falls on the one problem statement I heard it was really announces a problem statement, but it was a theme throughout all the breakout sessions in the keynotes, and you guys are aware of it. So it's not a surprise to the Del senior people. You guys recognize that as things are going well on the acquisition and the integration tell technologies there's still a focus on still working better with customers taking away the friction of doing business with del technologies. It's a hard problem statement. You guys are working the problem. What's your view on that? Because we hear that from your customers and partners we'd love work with. Kelly's going to get easier. We >> still have more work to do. Actually, Karen Contos and I are partnered up our chief customer officer on easy doing business and look it it. We are a complex company. We have a lot of different business units. Technologies brands were working toe, bring them together, and Mohr integrate solutions like we saw this week. But we still can be complex, sometimes in front of our customers, and we're working on that. It's a balance because on the one hand, customers want Maura line coordinated, sometimes single hand to shake. We get that. But the balance is they also want access to the right subject matter experts at the right time. And we don't want Teo inhibit that either. Either way, so whether it's with our customers directly with our partners were on that journey, we will find the right balance here. We've got new commercial contract mechanisms in place now to unify our Cordelia, AMC as we're packaging Mohr VM were content more security content into the offer and be able to delivered is a package solution. In one quote one order one service dogs doing some great thing and in the back end of services connecting our service request systems are CR M systems, actually, even with VM wear and Cordelia emcee technicians co locating and support centers to solve the custom of customers problem in one call, not in three calls. We still have a ways to go, but we are making progress. >> So I wanted to switch gears a little bit, and you and I, Howard have known each other for decades, and you've never wanted to talk about yourself. You always wanna talk about the team, your customers, your company. But I wanted to talk about your career a little bit because John Ferrier did an interview with John Chambers, and it was an amazing interview. We talked about when he was, you know, Wang and one one twenty eight. There is no entitlement, and you've seen a lot of the waves. You started out your career, your electrical engineer back when, you know that was like *** physics assembly language. It was sort of the early days of computer science, awesome, and then you had a number of different roles. You as I mentioned there was digital, there was compact. It was h p and then you'LL Forget RadioShack Radio second. Alright, That's right, Theo PC days on. And then you joined the emcee in two thousand three, which which marked the next era. We were coming out of the dot com boom, and You and Joe Tucci and a number of other executives built, you know, and the amazing next chapter of AMC powerhouse. And then now you're building the next new chapter with Del. You've really seen a lot of major industry shift you see have been on the wave. I wonder if you could reflect on that. Reflect on your career a little bit for our audience. >> I'm just amazed and blessed to be where I am. I couldn't be more pleased. Sometimes I wonder how even got here. But when I do reflect back, it is my love of the technology. It's my love of what technology Khun do for businesses, for customers, for consumers and, frankly, my love of the customer interaction. This is, you know, from that first time in the Radio Shack retail store and you know, the parent coming in and learning about this new TRS eighty and I've heard about this and what does this really mean and being able to help that person understand the use of the technology? How Teo, you make it happen for them, it has always given me great satisfaction. And so, you know, from those early days and I've worked with a lot of great people that I just, you know, listen and learn from over the time. But, you know, when I mentor, you know, people coming up in their career, I always say, Look, you know, it's not at work. If you get up every morning, you love what you do, you see the impact that you make you'LL like the people you're working with. You're making a little money and having some fun on DH. Those things have always been true for me. I have been so lucky and so blessed in life to be able to have that be the case >> and your operational to you understand, make operations work, solve problems, Day pointed out. It's been great for my first basic program I wrote was on a TRS eighty in high school. So thank you for getting those out here and then I've actually bought a Tandy, not an IBM with a ten Meg Hard drive. I bought my motive. Peces Unlimited. Some small company that was selling modems at the time. Michael, remember those date Howard? Great to have you on The key was the Distinguished Cube alumni. Great career and always we got We got it all documented. We have all the history. There you go, calling the shots. Howard Elias calling the future, predicting it and executing it Living is living the dream here in the Cube More keep coverage here, del technology world after >> this short break

>> Live, from San Francisco, it's theCUBE covering IBM Think 2019. Brought to you by IBM. >> Hello everyone, welcome back to theCUBE's live coverage here in San Francisco for IBM Think 2019. I'm John Furrier, Stu Miniman with theCUBE. Stu, it's been a great day. We're on our fourth day of four days of wall to wall coverage. A theme of AI, large scale compute with Cloud and data that's great. Great topics. Got two great guests here. Rohit Badlaney, who's the director of IBM Z As a Service, IBM Systems. Real great to see you. And Nataraj Nagaratnam, Distinguished Engineer and CTO and Director of Cloud Security at IBM and Hybrid Cloud, thanks for joining us. >> Glad to be here. >> So, the subtext to all the big messaging around AI and multi-cloud is that you need power to run this. Horsepower, you need big iron, you need the servers, you need the storage, but software is in the heart of all this. So you guys had some big announcements around capabilities. The Hyper Protect was a big one on the securities side but now you've got Z As a Service. We've seen Linux come on Z. So it's just another network now. It's just network computing is now tied in with cloud. Explain the offering. What's the big news? >> Sure, so two major announcements for us this week. One's around our private cloud capabilities on the platform. So we announced our IBM Cloud Private set of products fully supported on our LinuxOne systems, and what we've also announced is the extensions of those around hyper-secure workloads through a capability called the Secure Services Container, as well as giving our traditional z/OS clients cloud consumption through a capability called the z/OS Cloud Broker. So it's really looking at how do we cloudify the platform for our existing base, as well as clients looking to do digital transformation projects on-premise. How do we help them? >> This has been a key part of this. I want to just drill down this cloudification because we've been talking about how you guys are positioned for growth. All the REORG's are done. >> Sure, yeah >> The table's all set. Products have been modernized, upgraded. Now the path is pretty clear. Kind of like what Microsoft's playbook was. Build the core cloudification. Get your core set of products cloudified. Target your base of customers. Grow that and expand into the modern era. This is a key part of the strategy, right? >> Absolutely right. A key part of our private cloud strategy is targeted to our existing base and moving them forward on their cloud journey, whether they're looking to modernize parts of their application. Can we start first with where they are on-premise is really what we're after. >> Alright, also you have the Hyper Protect. >> Correct. >> What is that announcement? Can you explain Hyper Protect? >> Absolutely. Like Rohit talked about, taking our LinuxOne capabilities, now that enterprise trusts the level of assurance, the level of security that they're dependent on, on-premise and now in private cloud. We are taking that further into the public cloud offering as Hyper Protect services. So these are set of services that leverage the underlyings of security hardening that nobody else has the level of control that you can get and offering that as a service so you don't need to know Z or LinuxOne from a consumption perspective. So I'll take two examples. Hyper Protect Crypto Service is about exposing the level of control. That you can manage they keys. What we call "keep your own keys" because encryption is out there but it's all about key management so we provide that with the highest level of security that LinuxOne servers from us offer. Another example is database as a service, which runs in this Hyper Secure environment. Not only encryption and keys, but leveraging down the line pervasive encryption capabilities so nobody can even get into the box, so to say. >> Okay, so I get the encryption piece. That's solid, great. Internet encryption is always good. Containers, there's been discussions at the CNCF about containers not being part of the security boundaries and putting a VMware around it. Different schools of thought there. How do you guys look at the containerization? Does that fit into Secure Protect? Talk about that dynamic because encryption I get, but are you getting containers? >> Great question because it's about the workload, right? When people are modernizing their apps or building cloud-native apps, it's built on Kubernetes and containers. What we have done, the fantastic work across both the IBM Cloud Private on Z, as well as Hyper Protect, underlying it's all about containers, right? So as we deliver these services and for customers also to build data services as containers or VM's, they can deploy on this environment or consume these as a compute. So fundamentally it's kubernetes everywhere. That's a foundational focus for us. When it can go public, private and multicloud, and we are taking that journey into the most austere environment with a performance and scale of Z and LinuxONE. >> Alright, so Rohit, help bring us up to date. We've been talking about this hybrid and multi-cloud stuff for a number of years, and the idea we've heard for many years is, "I want to have the same stack on both ends. I want encryption all the way down to the chip set." I've heard of companies like Oracle, like IBM say, "We have resources in both. We want to do this." We understand kubernetes is not a magic layer, it takes care of a certain piece you know and we've been digging in that quite a bit. Super important, but there's more than that and there still are differences between what I'm doing in the private cloud and public cloud just naturally. Public cloud, I'm really limited to how many data centers, private cloud, everything's different. Help us understand what's the same, what's different. How do we sort that out in 2019? >> Sure, from a brand perspective we're looking at private cloud in our IBM Cloud Private set of products and standardizing on that from a kubernetes perspective, but also in a public cloud, we're standardizing on kubernetes. The key secret source is our Secure Services Container under there. It's the same technology that we use under our Blockchain Platform. Right, it brings the Z differentiation for hyper-security, lockdown, where you can run the most secure workloads, and we're standardizing that on both public and private cloud. Now, of course, there are key differences, right? We're standardizing on a different set of workloads on-premise. We're focusing on containerizing on-premise. That journey to move for the public cloud, we still need to get there. >> And the container piece is super important. Can you explain the piece around, if I've got multi-cloud going on, Z becomes a critical node on the network because if you have an on-premise base, Z's been very popular, LinuxONE has been really popular, but it's been for the big banks, and it seems like the big, you know, it's big ire, it's IBM, right? But it's not just the mainframe. It's not proprietary software anymore, it's essentially large-scale capability. >> Right. >> So now, when that gets factored into the pool of resources and cloud, how should customers look at Z? How should they look at the equation? Because this seems to me like an interesting vector into adding more head room for you guys, at least on the product side, but for a customer, it's not just a use case for the big banks, or doing big backups, it seems to have more legs now. Can you explain where this fits into the big picture? Because why wouldn't someone want to have a high performant? >> Why don't I use a customer example? I had a great session this morning with Brad Chun from Shuttle Fund, who joined us on stage. They know financial industry. They are building a Fintech capability called Digital Asset Custody Services. It's about how you digitize your asset, how do you tokenize them, how you secure it. So when they look at it from that perspective, they've been partnering with us, it's a classic hybrid workload where they've deployed some of the apps on the private cloud and on-premise with Z/LinuxONE and reaching out to the cloud using the Hyper Protect services. So when they bring this together, built on Blockchain under the covers, they're bringing the capability being agile to the market, the ability for them to innovate and deliver with speed, but with the level of capability. So from that perspective, it's a Fintech, but they are not the largest banks that you may know of, but that's the kind of innovation it enables, even if you don't have quote, unquote a mainframe or a Z. >> This gives you guys more power, and literally, sense of pretty more reach in the market because what containers and now these kubernetes, for example, Ginni Rometty said "kubernetes" twice in her keynote. I'm like, "Oh my God. The CEO of IBM said 'kubernetes' twice." We used to joke about it. Only geeks know about kubernetes. Here she is talking about kubernetes. Containers, kubernetes, and now service missions around the corner give you guys reach into the public cloud to extend the Z capability without foreclosing the benefits of Z. So that seems to be a trend. Who's the target for that? Give me an example of who's the customer or use case? What's the situation that would allow me to take advantage of cloud and extend the capability to Z? >> If you just step back, what we're really trying to do is create a higher shorten zone in our cloud called Hyper Protect. It's targeted to our existing Z base, who want to move on this enterprise out journey, but it's also targeted to clients like Shuttle Fund and DAX that Raj talked about that are building these hyper secure apps in the cloud and want the capabilities of the platform, but wanted more cloud-native style. It's the breadth of moving our existing base to the cloud, but also these new security developers who want to do enterprise development in the cloud. >> Security is key. That's the big drive. >> And that's the beauty of Z. That's what it brings to the table. And to a cloud is the hyper lockdown, the scale, the performance, all those characteristics. >> We know that security is always an on-going journey, but one of the ones that has a lot of people concerned is when we start adding IoT into the mix. It increased the surface area by orders of magnitude. How do those type of applications fit into these offerings? >> Great question. As a matter of fact, I didn't give you the question by the way, but this morning, KONE joined me on stage. >> We actually talked about it on Twitter. (laughs) >> KONE joined us on stage. It's about in the residential workflow, how they're enabling here their integration, access, and identity into that. As an example, they're building on our IoT platform and then they integrate with security services. That's the beauty of this. Rohit talked about developers, right? So when developers build it, our mission is to make it simple for a developer to build secure applications. With security skill shortage, you can't expect every developer to be a security geek, right? So we're making it simple, so that you can kind of connect your IoT to your business process and your back-end application seamlessly in a multi-cloud and hybrid-cloud fashion. That's where both from a cloud native perspective comes in, and building some of these sensitive applications on Hyper Protect or Z/LinuxONE and private cloud enables that end to end. >> I want to get you guys take while you're here because one of the things I've observed here at Think, which is clearly the theme is Cloud AI and developers all kind of coming together. I mean, AI, Amazon's event, AI, AI, AI, in cloud scale, you guys don't have that. But developer angle is really interesting. And you guys have a product called IBM Cloud Private, which seems to be a very big centerpiece of the strategy. What is this product? Why is it important? It seems to be part of all the key innovative parts that we see evolving out of the thing. Can you explain what is the IBM Cloud Private and how does it fit into the puzzle? >> Let me take a pass at it Raj. In a way it is, well, we really see IBM Cloud Private as that key linchpin on-premise. It's a Platform as a Service product on-premise, it's built on kubernetes and darker containers, but what it really brings is that standardized cloud consumption for containerized apps on-premise. We've expanded that, of course, to our Z footprint, and let me give you a use case of clients and how they use it. We're working with a very big, regulated bank that's looking to modernize a massive monolithic piece of WebSphere application server on-premise and break it down into micro-services. They're doing that on IBM Cloud Private. They've containerized big parts of the application on WebSphere on-premise. Now they've not made that journey to the cloud, to the public cloud, but they are using... How do you modernize your existing footprint into a more containerized micro-services one? >> So this is the trend we're seeing, the decomposition of monolithic apps on-premise is step one. Let's get that down, get the culture, and attract the new, younger people who come in, not the older guys like me, mini-computer days. Really make it ready, composable, then they're ready to go to the cloud. This seems to be the steps. Talk about that dynamic, Raj, from a technical perspective. How hard is it to do that? Is it a heavy lift? Is it pretty straight-forward? >> Great question. IBM, we're all about open, right? So when it comes to our cloud strategy open is the centerpiece offered, that's why we have banked on kubernetes and containers as that standardization layer. This way you can move a workflow from private to public, even ICP can be on other cloud vendors as well, not just IBM Cloud. So it's a private cloud that customers can manage, or in the public cloud or IBM kubernetes that we manage for them. Then it's about the app, the containerized app that can be moved around and that's where our announcements about Multicloud Manager, that we made late last year come into play, which helps you seamlessly move and integrate applications that are deployed on communities across private, public or multicloud. So that abstraction venire enables that to happen and that's why the open... >> So it's an operational construct? Not an IBM product, per say, if you think about it that way. So the question I have for you, I know Stu wants to jump in, he's got some questions. I want to get to this new mindset. The world's flipped upside down. The applications and workloads are dictating architecture and programmability to the DevOps, or infrastructure, in this case, Z or cloud. This is changing the game on how the cloud selection is. So we've been having a debate on theCUBE here, publicly, that in some cases it's the best cloud for the job decision, not a procurement, "I need multi-vendor cloud," versus I have a workload that runs best with this cloud. And it might be as if you're running 365, or G Suite as Google, Amazon's got something so it seems to be the trend. Do you agree with that? And certainly, there'll be many clouds. We think that's true, it's already happened. Your thoughts on this workload driving the requirements for the cloud? Whether it's a sole purpose cloud, meaning for the app. >> That's right. I'll start and Rohit will add in as well. That's where this chapter two comes into play, as we call Chapter Two of Cloud because it is about how do you take enterprise applications, the mission-critical complex workloads, and then look for the enablers. How do you make that modernization seamless? How do you make the cloud native seamless? So in that particular journey, is where IBM cloud and our Multicloud and Hybrid Cloud strategy come into play to make that transition happen and provide the set of capabilities that enterprises are looking for to move their critical workloads across private and public in bit much more assurance and performance and scale, and that's where the work that we are doing with Z, LinuxONE set of as an underpinning to embark on the journey to move those critical workloads to their cloud. So you're absolutely right. When they look at which cloud to go, it's about capabilities, the tools, the management orchestration layers that a cloud provider or a cloud vendor provide and it's not only just about IBM Public Cloud, but it's about enabling the enterprises to provide them the choice and then offer. >> So it's not multicloud for multicloud sake, it's multicloud, that's the reality. Workload drives the functionality. >> Absolutely. We see that as well. >> Validated on theCUBE by the gurus of IBM. The cloud for the job is the best solution. >> So I guess to kind of put a bow on this, the journey we're having is talking about distributed architectures, and you know, we're down on the weeds, we've got micro-services architectures, containerization, and we're working at making those things more secure. Obviously, there's still a little bit more work to do there, but what's next is we look forward, what are the challenges customers have. They live in this, you know, heterogeneous multicloud world. What do we have to do as an industry? Where is IBM making sure that they have a leadership position? >> From my perspective, I think really the next big wave of cloud is going to be looking at those enterprise workloads. It's funny, I was just having a conversation with a very big bank in the Netherlands, and they were, of course, a very big Z client, and asking us about the breadth of our cloud strategy and how they can move forward. Really looking at a private cloud strategy helping them modernize, and then looking at which targeted workloads they could move to public cloud is going to be the next frontier. And those 80 percent of workloads that haven't moved. >> An integration is key, and for you guys competitive strategy-wise, you've got a lot of business applications running on IBM's huge customer base. Focus on those. >> Yes. >> And then give them the path to the cloud. The integration piece is where the linchpin is and OSSI secure. >> Enterprise out guys. >> Love encryption, love to follow up more on the secure container thing, I think that's a great topic. We'll follow-up after this show Raj. Thanks for coming on. theCUBE coverage here. I'm John Furrier, Stu Miniman. Live coverage, day four, here live in San Francisco for IBM Think 2019. Stay with us more. Our next guests will be here right after a short break. (upbeat music)

>> Announcer: Live from Las Vegas, it's theCUBE, covering NetApp Insight 2018. Brought to you by NetApp. >> Welcome back to theCUBE, we're live at NetApp Insight 2018 from the Mandalay Bay, in Las Vegas, I'm Lisa Martin, my co-host for the day is Stu Miniman. We're welcoming back two distinguished alumni to theCUBE, we've got Anthony Lye SVP and GM of the Cloud BU at NetApp. Hey, Anthony, welcome back. >> Hello, thank you very much. >> Fresh from the keynote stage. And we've also got a Tad Brockway, the head of product Azure Storage, Media and Edge at Microsoft, Tad, welcome back. >> Yeah, thank you. >> So guys, this is day one, keynote this morning, it was standing room only, 5,000 plus people here, Jean English was on your CMO of NetApp and said, most ever customers and partners under one roof at NetApp. So that's exciting. Let's talk about partnerships. NetApp has been around 26 years and the slide of partners and sponsors this morning was like a NASCAR slide. Tell us Anthony, about what you guys are doing, and how you're evolving your relationship with Microsoft? >> Oh, I mean, I think of all the relationships, Microsoft is unique. Tad and I have worked together now for over a year. >> Yeah, yeah. >> And it's an engineering relationship. There is absolutely no doubt about it. We are doing things in Azure that nobody else has ever done. I think we sort of bring 26 years of NetApp experience to the infinite possibilities that Azure brings to its customers. It's transformation based on, very reliable infrastructure. So you get all the forward looking values of Azure, complemented by the 26 years of NetApp. >> Yeah, it's a great way to-- >> So a year ago, at this very event, NetApp Insight 2017, you announced some exciting things. One of them being Azure NetApp files. >> Anthony: Correct. >> Tell us about, a year later, where you are with that? I know McKesson, big brand in healthcare, they're going to be on stage tomorrow, give us a little bit of perspective about what that announcement has transformed into, one year in? >> Well, let me give you my perspective and then Tad, you should obviously give the view of Microsoft. For NetApp, it's given our customers confidence and confidence in their choice of public Cloud, that they now feel that Azure has distinct advantage in that it can land workloads that today currently run on NetApp. And they have the confidence that Microsoft has selected NetApp, that Microsoft will sell the service, Microsoft will support the service, Microsoft will build the service. I think we've also done something quite unique in the way the service is delivered. We could have just thrown up storage and said to customers, "You manage it." But I think together, we wanted to try and provide almost like dial tone, we just wanted storage to be there, and we wanted to give people performance guarantee. So they felt very comfortable picking a particular performance level with a particular workload. And that's not been done before. So, we're seeing fantastic results from customers, we have a backlog that's growing by the day, and customers who have been onboarded onto the system, have rave things to say about it. You'll hear from one of those customers tomorrow on stage with Tad and I. But Tad, how would you characterize the year? >> Yeah, sure. So, a lot of engineering effort, and that's the thing that makes this, customers don't care about how something is implemented, they care about the value that they get out of it. But it's because we've put so much effort into this across our companies, from an engineering standpoint, that there's nothing like this in the industry today. As we roll this out into Azure regions around the world, it is going to be a highly differentiated offering. And that's because fundamentally, what we're doing is, we're bringing Azure NetApp into Microsoft data centers, and we're wiring NetApp ONTAP directly into Azure. So we've worked together on the design for some advanced networking capability, all the way down to the switch level, where we have very low latency, very high throughput from the Azure Public Cloud, all of the infrastructure, all of the customers VMs, directly into ONTAP, very low latency, very high bandwidth. So all of the performance characteristics of ONTAP on-prem, and then bringing that into the Public Cloud. So you get really a no compromise transformation for your existing apps and you get the ability to provision that app volumes in a way that is fundamentally unique, it fits with the whole Cloud paradigm of being able to pay for your resources as you go, the democratization of IT so that individual business units can go provision volumes. So it really is Cloud paradigm plus all of the performance capabilities of ONTAP. >> I wonder if we can unpack that a little bit. When I think about Microsoft and NetApp, you both have really, it's called today Hybrid Multi Cloud. But Microsoft it's been given a lot of credit that it's got a strong Hybrid strategy. When I think back, I mean, Microsoft's always had storage as part of the Stack. If today, and Azure Stack, you've got Storage Spaces Direct, you've got a Cloud first strategy. So I want to be able to do the same thing in public Azure as when I'm building solutions, put it in the environment, can you help connect, where does that this ONTAP solution fit in there? Because, some people would say, "Well, come on Microsoft, "wouldn't you just build this with your own solutions?" Why do you turn to NetApp? >> So, it's true, I guess, the spirit, I think the spirit of what you're asking is, it's an observation that what brings our companies together is an appreciation for enterprise customers being able to do things on their terms. That involves customers taking existing IT workloads and then transforming them over to the cloud, as opposed to zeroing everything out and starting over, that's just not realistic. So, it's the strategy for Microsoft and the strategy for NetApp, and then our partnership together to meet customers where they are, help them evolve. So scenarios like Hybrid, they fit very nicely within that and Microsoft's portfolio with Azure Stack and some of the other things that we're doing there with Data Box, and so on. These are edge investments that are intended to extend the reach of Cloud into customer environments. And then to make it really easy for customers to take their existing assets, and then take advantage of the Cloud. That fits with the whole model of what we're doing with ONTAP as well. >> Anthony, we would love to hear your piece because there's NetApp pieces that are going into the Cloud but we see Microsoft, the Cloud is the starting point, we start in the public Cloud, and then that pushes out to the edge. >> Yeah, I think, I would make two points, I think, just to reinforce what Tad said, that there's just a technology that sits behind the file system that you cannot underestimate the importance of what Dave Hitz really started. I mean, ONTAP does things that no other file system can do. It manages the data in a very particular way, it allows us to run NFS and SMB protocols on the same volume for certain use cases. It has almost linear performance throughput characteristics. And we've been able to take that file system and then build intellectual property for certain workloads. So, NetApp is really the most commonly deployed platform for SAP. We are probably still the biggest platform for Oracle Database deployment, for MySQL deployment. So I think there's a technology, I think there is a sort of a history and legacy in Linux and open source based workloads, that we have an understanding of that adds to Microsoft. Now, the second point I would say is, I personally agree very much with Tad, but I think what you're going to see is IT will be redefined by Cloud. What I mean by that is, the Cloud will essentially establish the baseline and then push itself and it's sort of it's own access control lists, security models, those will end up getting pushed back to IT. So I think you're going to see a Cloud defined IT business as opposed to an IT defined Cloud. >> Yeah, I buy that. >> And I think there's just so much elegance and simplicity and scalability in Azure. Now, they had 25 years of watching everybody else make a mess of legacy IT, and now Azure is such a pure environment that it can extend, I think, and provide tons of value outside of Azure. >> So you guys mentioned, I think, Anthony, you mentioned when we kicked off, that this is really kind of an engineering partnership, when if we look at the history that both NetApp and Microsoft, have massive install basis of customers, customers that didn't start out in the digital era, obviously, customers that are born in that too. I'm curious, you mentioned about IT, from a joint selling standpoint, where are these conversations initiating? Are you talking with the IT folks? Are you going to the business folks who are having a more business outcomes led conversation? So Anthony, I will start with you? >> Well, so I would say, my favorite line about Cloud was, actually a line Marc Benioff quoted which was, what Clouds do is they democratize innovation. And if you think about that for a second, the environments that we grew up in, the big companies had a material advantage in their use of technology. The small companies couldn't afford to do it. You look at Azure now, and any single person on the planet can consume Azure. They don't need permission, in many cases, and ideas that would never get through the business case, can now be started on Azure. And there are so many great ideas and concepts that needed that sort of easy onboarding and services that, machine learning and artificial intelligence, there's a handful of companies that could buy that stuff themselves. Azure gives you access to all of that. So I think what's happening is that democratization has sort of infused more buyers. So what used to be a fairly linear process through the CIO has now been fractured. A lot of application developers are buying by themselves. Line of business people are funding project work sometimes without IT's knowledge. So for us, we wanted to make sure that we could allow traditional customers to extend to Azure, traditional customers to migrate to Azure, but we wanted to build a service that would appeal to the new Cloud buyer. To the application developer, to the data scientist. And I think we've done a very good job doing that. >> Yeah, no, I agree. I think, it's the combination of empowering folks to go do things to increase productivity at the individual business unit level, but then do that with technology that has taken decades of thousands of engineers to develop. This combination, there really is nothing like it in the industry, it's really unique. >> At lunch, I was talking to a couple of users here, and they were a little bit nervous, a little bit excited, going to go through some sort of Cloud certification. Cloud is an opportunity for a lot of people to scale up on new skill sets. I'm sure there's new certification. Can you talk a little bit about how you're helping customers move towards the future? >> Yeah, I think we've sort of, in many ways made, ONTAP, very much a relevant service in Azure and what we hope that means is for all of the people that have been very loyal to NetApp and to ONTAP that their skill set now translates into the Cloud compensations. One of the things we'll say, on stage tomorrow is, Microsoft and NetApp have worked together to create a certification that blends the best of what ONTAP can do for workloads, strategy and design with the wealth of services that Azure has. It's awesome to be onstage with Tad, we provide a critical service, but Microsoft has how many services now, in Azure? >> Tad: Oh, Gosh, hundreds. >> Hundreds and hundreds of services. And as a developer, I feel, you're like a kid in a candy store when you're in Azure, you can switch on almost anything and find services that will do incredible things that you could never get from IT. You could just never get those services. What Microsoft has is a scale so vast, I mean, how many data centers will you be at, by the end of the year? >> Well, we're in 54 regions today, and then each region has multiple data centers. >> Anthony: Hundreds. >> So anyway, we're all over the planet. >> So guys, we're out of time, but just really quickly, so we've seen this evolution, you guys have lived this evolution in the last year. The public preview is out for-- >> Azure NetApp files. >> Azure NetApp files, any Sneak Peek you can give us into what some of your customers are going to be saying tomorrow about the business outcomes like, reducing costs, or speed of transactions, that are going to be here tomorrow? >> You should get Brad up here from McKesson because he's awesome. Brad's been on point for it and I think, you'll hear from a customer tomorrow that they plan to bring the biggest enterprise workloads to Azure. I mean, I think when he names the applications, they are non-trivial applications that couldn't move, but now with Azure Netapp files can. I think he's also going to say that as well as benchmarking very well at the big workloads, we actually benchmark very well on the cost curve. That we can migrate workloads and give very good cost, I think characteristics as well as performance. So we've tried to give people that two dimensional flexibility. >> Well, that's going to be something not to miss. So if you're here at NetApp Insight, check it out, if you're not, watch it on their live stream. Tad, Anthony, thanks so much for joining-- >> Thank you, very much. >> Stu and me and sharing with us the momentum and the vision that you're now seeing manifest. We appreciate your time. >> Perfect, thank you. >> From Stu Miniman and I'm Lisa Martin, you're watching theCUBE Live from Las Vegas, NetApp Insight 2018, stick around we'll be back after a short break.

>> Announcer: Live from New York City it's The Cube, covering IBM data science for all. Brought to you by IBM. (light digital music) >> Welcome back to data science for all. It's a whole new game. And it is a whole new game. >> Dave Vellante, John Walls here. We've got quite a distinguished panel. So it is a new game-- >> Well we're in the game, I'm just happy to be-- (both laugh) Have a swing at the pitch. >> Well let's what we have here. Five distinguished members of our panel. It'll take me a minute to get through the introductions, but believe me they're worth it. Jennifer Shin joins us. Jennifer's the founder of 8 Path Solutions, the director of the data science of Comcast and part of the faculty at UC Berkeley and NYU. Jennifer, nice to have you with us, we appreciate the time. Joe McKendrick an analyst and contributor of Forbes and ZDNet, Joe, thank you for being here at well. Another ZDNetter next to him, Dion Hinchcliffe, who is a vice president and principal analyst of Constellation Research and also contributes to ZDNet. Good to see you, sir. To the back row, but that doesn't mean anything about the quality of the participation here. Bob Hayes with a killer Batman shirt on by the way, which we'll get to explain in just a little bit. He runs the Business over Broadway. And Joe Caserta, who the founder of Caserta Concepts. Welcome to all of you. Thanks for taking the time to be with us. Jennifer, let me just begin with you. Obviously as a practitioner you're very involved in the industry, you're on the academic side as well. We mentioned Berkeley, NYU, steep experience. So I want you to kind of take your foot in both worlds and tell me about data science. I mean where do we stand now from those two perspectives? How have we evolved to where we are? And how would you describe, I guess the state of data science? >> Yeah so I think that's a really interesting question. There's a lot of changes happening. In part because data science has now become much more established, both in the academic side as well as in industry. So now you see some of the bigger problems coming out. People have managed to have data pipelines set up. But now there are these questions about models and accuracy and data integration. So the really cool stuff from the data science standpoint. We get to get really into the details of the data. And I think on the academic side you now see undergraduate programs, not just graduate programs, but undergraduate programs being involved. UC Berkeley just did a big initiative that they're going to offer data science to undergrads. So that's a huge news for the university. So I think there's a lot of interest from the academic side to continue data science as a major, as a field. But I think in industry one of the difficulties you're now having is businesses are now asking that question of ROI, right? What do I actually get in return in the initial years? So I think there's a lot of work to be done and just a lot of opportunity. It's great because people now understand better with data sciences, but I think data sciences have to really think about that seriously and take it seriously and really think about how am I actually getting a return, or adding a value to the business? >> And there's lot to be said is there not, just in terms of increasing the workforce, the acumen, the training that's required now. It's a still relatively new discipline. So is there a shortage issue? Or is there just a great need? Is the opportunity there? I mean how would you look at that? >> Well I always think there's opportunity to be smart. If you can be smarter, you know it's always better. It gives you advantages in the workplace, it gets you an advantage in academia. The question is, can you actually do the work? The work's really hard, right? You have to learn all these different disciplines, you have to be able to technically understand data. Then you have to understand it conceptually. You have to be able to model with it, you have to be able to explain it. There's a lot of aspects that you're not going to pick up overnight. So I think part of it is endurance. Like are people going to feel motivated enough and dedicate enough time to it to get very good at that skill set. And also of course, you know in terms of industry, will there be enough interest in the long term that there will be a financial motivation. For people to keep staying in the field, right? So I think it's definitely a lot of opportunity. But that's always been there. Like I tell people I think of myself as a scientist and data science happens to be my day job. That's just the job title. But if you are a scientist and you work with data you'll always want to work with data. I think that's just an inherent need. It's kind of a compulsion, you just kind of can't help yourself, but dig a little bit deeper, ask the questions, you can't not think about it. So I think that will always exist. Whether or not it's an industry job in the way that we see it today, and like five years from now, or 10 years from now. I think that's something that's up for debate. >> So all of you have watched the evolution of data and how it effects organizations for a number of years now. If you go back to the days when data warehouse was king, we had a lot of promises about 360 degree views of the customer and how we were going to be more anticipatory in terms and more responsive. In many ways the decision support systems and the data warehousing world didn't live up to those promises. They solved other problems for sure. And so everybody was looking for big data to solve those problems. And they've begun to attack many of them. We talked earlier in The Cube today about fraud detection, it's gotten much, much better. Certainly retargeting of advertising has gotten better. But I wonder if you could comment, you know maybe start with Joe. As to the effect that data and data sciences had on organizations in terms of fulfilling that vision of a 360 degree view of customers and anticipating customer needs. >> So. Data warehousing, I wouldn't say failed. But I think it was unfinished in order to achieve what we need done today. At the time I think it did a pretty good job. I think it was the only place where we were able to collect data from all these different systems, have it in a single place for analytics. The big difference between what I think, between data warehousing and data science is data warehouses were primarily made for the consumer to human beings. To be able to have people look through some tool and be able to analyze data manually. That really doesn't work anymore, there's just too much data to do that. So that's why we need to build a science around it so that we can actually have machines actually doing the analytics for us. And I think that's the biggest stride in the evolution over the past couple of years, that now we're actually able to do that, right? It used to be very, you know you go back to when data warehouses started, you had to be a deep technologist in order to be able to collect the data, write the programs to clean the data. But now you're average causal IT person can do that. Right now I think we're back in data science where you have to be a fairly sophisticated programmer, analyst, scientist, statistician, engineer, in order to do what we need to do, in order to make machines actually understand the data. But I think part of the evolution, we're just in the forefront. We're going to see over the next, not even years, within the next year I think a lot of new innovation where the average person within business and definitely the average person within IT will be able to do as easily say, "What are my sales going to be next year?" As easy as it is to say, "What were my sales last year." Where now it's a big deal. Right now in order to do that you have to build some algorithms, you have to be a specialist on predictive analytics. And I think, you know as the tools mature, as people using data matures, and as the technology ecosystem for data matures, it's going to be easier and more accessible. >> So it's still too hard. (laughs) That's something-- >> Joe C.: Today it is yes. >> You've written about and talked about. >> Yeah no question about it. We see this citizen data scientist. You know we talked about the democratization of data science but the way we talk about analytics and warehousing and all the tools we had before, they generated a lot of insights and views on the information, but they didn't really give us the science part. And that's, I think that what's missing is the forming of the hypothesis, the closing of the loop of. We now have use of this data, but are are changing, are we thinking about it strategically? Are we learning from it and then feeding that back into the process. I think that's the big difference between data science and the analytics side. But, you know just like Google made search available to everyone, not just people who had highly specialized indexers or crawlers. Now we can have tools that make these capabilities available to anyone. You know going back to what Joe said I think the key thing is we now have tools that can look at all the data and ask all the questions. 'Cause we can't possibly do it all ourselves. Our organizations are increasingly awash in data. Which is the life blood of our organizations, but we're not using it, you know this a whole concept of dark data. And so I think the concept, or the promise of opening these tools up for everyone to be able to access those insights and activate them, I think that, you know, that's where it's headed. >> This is kind of where the T shirt comes in right? So Bob if you would, so you've got this Batman shirt on. We talked a little bit about it earlier, but it plays right into what Dion's talking about. About tools and, I don't want to spoil it, but you go ahead (laughs) and tell me about it. >> Right, so. Batman is a super hero, but he doesn't have any supernatural powers, right? He can't fly on his own, he can't become invisible on his own. But the thing is he has the utility belt and he has these tools he can use to help him solve problems. For example he as the bat ring when he's confronted with a building that he wants to get over, right? So he pulls it out and uses that. So as data professionals we have all these tools now that these vendors are making. We have IBM SPSS, we have data science experience. IMB Watson that these data pros can now use it as part of their utility belt and solve problems that they're confronted with. So if you''re ever confronted with like a Churn problem and you have somebody who has access to that data they can put that into IBM Watson, ask a question and it'll tell you what's the key driver of Churn. So it's not that you have to be a superhuman to be a data scientist, but these tools will help you solve certain problems and help your business go forward. >> Joe McKendrick, do you have a comment? >> Does that make the Batmobile the Watson? (everyone laughs) Analogy? >> I was just going to add that, you know all of the billionaires in the world today and none of them decided to become Batman yet. It's very disappointing. >> Yeah. (Joe laughs) >> Go ahead Joe. >> And I just want to add some thoughts to our discussion about what happened with data warehousing. I think it's important to point out as well that data warehousing, as it existed, was fairly successful but for larger companies. Data warehousing is a very expensive proposition it remains a expensive proposition. Something that's in the domain of the Fortune 500. But today's economy is based on a very entrepreneurial model. The Fortune 500s are out there of course it's ever shifting. But you have a lot of smaller companies a lot of people with start ups. You have people within divisions of larger companies that want to innovate and not be tied to the corporate balance sheet. They want to be able to go through, they want to innovate and experiment without having to go through finance and the finance department. So there's all these open source tools available. There's cloud resources as well as open source tools. Hadoop of course being a prime example where you can work with the data and experiment with the data and practice data science at a very low cost. >> Dion mentioned the C word, citizen data scientist last year at the panel. We had a conversation about that. And the data scientists on the panel generally were like, "Stop." Okay, we're not all of a sudden going to turn everybody into data scientists however, what we want to do is get people thinking about data, more focused on data, becoming a data driven organization. I mean as a data scientist I wonder if you could comment on that. >> Well I think so the other side of that is, you know there are also many people who maybe didn't, you know follow through with science, 'cause it's also expensive. A PhD takes a lot of time. And you know if you don't get funding it's a lot of money. And for very little security if you think about how hard it is to get a teaching job that's going to give you enough of a pay off to pay that back. Right, the time that you took off, the investment that you made. So I think the other side of that is by making data more accessible, you allow people who could have been great in science, have an opportunity to be great data scientists. And so I think for me the idea of citizen data scientist, that's where the opportunity is. I think in terms of democratizing data and making it available for everyone, I feel as though it's something similar to the way we didn't really know what KPIs were, maybe 20 years ago. People didn't use it as readily, didn't teach it in schools. I think maybe 10, 20 years from now, some of the things that we're building today from data science, hopefully more people will understand how to use these tools. They'll have a better understanding of working with data and what that means, and just data literacy right? Just being able to use these tools and be able to understand what data's saying and actually what it's not saying. Which is the thing that most people don't think about. But you can also say that data doesn't say anything. There's a lot of noise in it. There's too much noise to be able to say that there is a result. So I think that's the other side of it. So yeah I guess in terms for me, in terms of data a serious data scientist, I think it's a great idea to have that, right? But at the same time of course everyone kind of emphasized you don't want everyone out there going, "I can be a data scientist without education, "without statistics, without math," without understanding of how to implement the process. I've seen a lot of companies implement the same sort of process from 10, 20 years ago just on Hadoop instead of SQL. Right and it's very inefficient. And the only difference is that you can build more tables wrong than they could before. (everyone laughs) Which is I guess >> For less. it's an accomplishment and for less, it's cheaper, yeah. >> It is cheaper. >> Otherwise we're like I'm not a data scientist but I did stay at a Holiday Inn Express last night, right? >> Yeah. (panelists laugh) And there's like a little bit of pride that like they used 2,000, you know they used 2,000 computers to do it. Like a little bit of pride about that, but you know of course maybe not a great way to go. I think 20 years we couldn't do that, right? One computer was already an accomplishment to have that resource. So I think you have to think about the fact that if you're doing it wrong, you're going to just make that mistake bigger, which his also the other side of working with data. >> Sure, Bob. >> Yeah I have a comment about that. I've never liked the term citizen data scientist or citizen scientist. I get the point of it and I think employees within companies can help in the data analytics problem by maybe being a data collector or something. I mean I would never have just somebody become a scientist based on a few classes here she takes. It's like saying like, "Oh I'm going to be a citizen lawyer." And so you come to me with your legal problems, or a citizen surgeon. Like you need training to be good at something. You can't just be good at something just 'cause you want to be. >> John: Joe you wanted to say something too on that. >> Since we're in New York City I'd like to use the analogy of a real scientist versus a data scientist. So real scientist requires tools, right? And the tools are not new, like microscopes and a laboratory and a clean room. And these tools have evolved over years and years, and since we're in New York we could walk within a 10 block radius and buy any of those tools. It doesn't make us a scientist because we use those tools. I think with data, you know making, making the tools evolve and become easier to use, you know like Bob was saying, it doesn't make you a better data scientist, it just makes the data more accessible. You know we can go buy a microscope, we can go buy Hadoop, we can buy any kind of tool in a data ecosystem, but it doesn't really make you a scientist. I'm very involved in the NYU data science program and the Columbia data science program, like these kids are brilliant. You know these kids are not someone who is, you know just trying to run a day to day job, you know in corporate America. I think the people who are running the day to day job in corporate America are going to be the recipients of data science. Just like people who take drugs, right? As a result of a smart data scientist coming up with a formula that can help people, I think we're going to make it easier to distribute the data that can help people with all the new tools. But it doesn't really make it, you know the access to the data and tools available doesn't really make you a better data scientist. Without, like Bob was saying, without better training and education. >> So how-- I'm sorry, how do you then, if it's not for everybody, but yet I'm the user at the end of the day at my company and I've got these reams of data before me, how do you make it make better sense to me then? So that's where machine learning comes in or artificial intelligence and all this stuff. So how at the end of the day, Dion? How do you make it relevant and usable, actionable to somebody who might not be as practiced as you would like? >> I agree with Joe that many of us will be the recipients of data science. Just like you had to be a computer science at one point to develop programs for a computer, now we can get the programs. You don't need to be a computer scientist to get a lot of value out of our IT systems. The same thing's going to happen with data science. There's far more demand for data science than there ever could be produced by, you know having an ivory tower filled with data scientists. Which we need those guys, too, don't get me wrong. But we need to have, productize it and make it available in packages such that it can be consumed. The outputs and even some of the inputs can be provided by mere mortals, whether that's machine learning or artificial intelligence or bots that go off and run the hypotheses and select the algorithms maybe with some human help. We have to productize it. This is a constant of data scientist of service, which is becoming a thing now. It's, "I need this, I need this capability at scale. "I need it fast and I need it cheap." The commoditization of data science is going to happen. >> That goes back to what I was saying about, the recipient also of data science is also machines, right? Because I think the other thing that's happening now in the evolution of data is that, you know the data is, it's so tightly coupled. Back when you were talking about data warehousing you have all the business transactions then you take the data out of those systems, you put them in a warehouse for analysis, right? Maybe they'll make a decision to change that system at some point. Now the analytics platform and the business application is very tightly coupled. They become dependent upon one another. So you know people who are using the applications are now be able to take advantage of the insights of data analytics and data science, just through the app. Which never really existed before. >> I have one comment on that. You were talking about how do you get the end user more involved, well like we said earlier data science is not easy, right? As an end user, I encourage you to take a stats course, just a basic stats course, understanding what a mean is, variability, regression analysis, just basic stuff. So you as an end user can get more, or glean more insight from the reports that you're given, right? If you go to France and don't know French, then people can speak really slowly to you in French, you're not going to get it. You need to understand the language of data to get value from the technology we have available to us. >> Incidentally French is one of the languages that you have the option of learning if you're a mathematicians. So math PhDs are required to learn a second language. France being the country of algebra, that's one of the languages you could actually learn. Anyway tangent. But going back to the point. So statistics courses, definitely encourage it. I teach statistics. And one of the things that I'm finding as I go through the process of teaching it I'm actually bringing in my experience. And by bringing in my experience I'm actually kind of making the students think about the data differently. So the other thing people don't think about is the fact that like statisticians typically were expected to do, you know, just basic sort of tasks. In a sense that they're knowledge is specialized, right? But the day to day operations was they ran some data, you know they ran a test on some data, looked at the results, interpret the results based on what they were taught in school. They didn't develop that model a lot of times they just understand what the tests were saying, especially in the medical field. So when you when think about things like, we have words like population, census. Which is when you take data from every single, you have every single data point versus a sample, which is a subset. It's a very different story now that we're collecting faster than it used to be. It used to be the idea that you could collect information from everyone. Like it happens once every 10 years, we built that in. But nowadays you know, you know here about Facebook, for instance, I think they claimed earlier this year that their data was more accurate than the census data. So now there are these claims being made about which data source is more accurate. And I think the other side of this is now statisticians are expected to know data in a different way than they were before. So it's not just changing as a field in data science, but I think the sciences that are using data are also changing their fields as well. >> Dave: So is sampling dead? >> Well no, because-- >> Should it be? (laughs) >> Well if you're sampling wrong, yes. That's really the question. >> Okay. You know it's been said that the data doesn't lie, people do. Organizations are very political. Oftentimes you know, lies, damned lies and statistics, Benjamin Israeli. Are you seeing a change in the way in which organizations are using data in the context of the politics. So, some strong P&L manager say gets data and crafts it in a way that he or she can advance their agenda. Or they'll maybe attack a data set that is, probably should drive them in a different direction, but might be antithetical to their agenda. Are you seeing data, you know we talked about democratizing data, are you seeing that reduce the politics inside of organizations? >> So you know we've always used data to tell stories at the top level of an organization that's what it's all about. And I still see very much that no matter how much data science or, the access to the truth through looking at the numbers that story telling is still the political filter through which all that data still passes, right? But it's the advent of things like Block Chain, more and more corporate records and corporate information is going to end up in these open and shared repositories where there is not alternate truth. It'll come back to whoever tells the best stories at the end of the day. So I still see the organizations are very political. We are seeing now more open data though. Open data initiatives are a big thing, both in government and in the private sector. It is having an effect, but it's slow and steady. So that's what I see. >> Um, um, go ahead. >> I was just going to say as well. Ultimately I think data driven decision making is a great thing. And it's especially useful at the lower tiers of the organization where you have the routine day to day's decisions that could be automated through machine learning and deep learning. The algorithms can be improved on a constant basis. On the upper levels, you know that's why you pay executives the big bucks in the upper levels to make the strategic decisions. And data can help them, but ultimately, data, IT, technology alone will not create new markets, it will not drive new businesses, it's up to human beings to do that. The technology is the tool to help them make those decisions. But creating businesses, growing businesses, is very much a human activity. And that's something I don't see ever getting replaced. Technology might replace many other parts of the organization, but not that part. >> I tend to be a foolish optimist when it comes to this stuff. >> You do. (laughs) >> I do believe that data will make the world better. I do believe that data doesn't lie people lie. You know I think as we start, I'm already seeing trends in industries, all different industries where, you know conventional wisdom is starting to get trumped by analytics. You know I think it's still up to the human being today to ignore the facts and go with what they think in their gut and sometimes they win, sometimes they lose. But generally if they lose the data will tell them that they should have gone the other way. I think as we start relying more on data and trusting data through artificial intelligence, as we start making our lives a little bit easier, as we start using smart cars for safety, before replacement of humans. AS we start, you know, using data really and analytics and data science really as the bumpers, instead of the vehicle, eventually we're going to start to trust it as the vehicle itself. And then it's going to make lying a little bit harder. >> Okay, so great, excellent. Optimism, I love it. (John laughs) So I'm going to play devil's advocate here a little bit. There's a couple elephant in the room topics that I want to, to explore a little bit. >> Here it comes. >> There was an article today in Wired. And it was called, Why AI is Still Waiting for It's Ethics Transplant. And, I will just read a little segment from there. It says, new ethical frameworks for AI need to move beyond individual responsibility to hold powerful industrial, government and military interests accountable as they design and employ AI. When tech giants build AI products, too often user consent, privacy and transparency are overlooked in favor of frictionless functionality that supports profit driven business models based on aggregate data profiles. This is from Kate Crawford and Meredith Whittaker who founded AI Now. And they're calling for sort of, almost clinical trials on AI, if I could use that analogy. Before you go to market you've got to test the human impact, the social impact. Thoughts. >> And also have the ability for a human to intervene at some point in the process. This goes way back. Is everybody familiar with the name Stanislav Petrov? He's the Soviet officer who back in 1983, it was in the control room, I guess somewhere outside of Moscow in the control room, which detected a nuclear missile attack against the Soviet Union coming out of the United States. Ordinarily I think if this was an entirely AI driven process we wouldn't be sitting here right now talking about it. But this gentlemen looked at what was going on on the screen and, I'm sure he's accountable to his authorities in the Soviet Union. He probably got in a lot of trouble for this, but he decided to ignore the signals, ignore the data coming out of, from the Soviet satellites. And as it turned out, of course he was right. The Soviet satellites were seeing glints of the sun and they were interpreting those glints as missile launches. And I think that's a great example why, you know every situation of course doesn't mean the end of the world, (laughs) it was in this case. But it's a great example why there needs to be a human component, a human ability for human intervention at some point in the process. >> So other thoughts. I mean organizations are driving AI hard for profit. Best minds of our generation are trying to figure out how to get people to click on ads. Jeff Hammerbacher is famous for saying it. >> You can use data for a lot of things, data analytics, you can solve, you can cure cancer. You can make customers click on more ads. It depends on what you're goal is. But, there are ethical considerations we need to think about. When we have data that will have a racial bias against blacks and have them have higher prison sentences or so forth or worse credit scores, so forth. That has an impact on a broad group of people. And as a society we need to address that. And as scientists we need to consider how are we going to fix that problem? Cathy O'Neil in her book, Weapons of Math Destruction, excellent book, I highly recommend that your listeners read that book. And she talks about these issues about if AI, if algorithms have a widespread impact, if they adversely impact protected group. And I forget the last criteria, but like we need to really think about these things as a people, as a country. >> So always think the idea of ethics is interesting. So I had this conversation come up a lot of times when I talk to data scientists. I think as a concept, right as an idea, yes you want things to be ethical. The question I always pose to them is, "Well in the business setting "how are you actually going to do this?" 'Cause I find the most difficult thing working as a data scientist, is to be able to make the day to day decision of when someone says, "I don't like that number," how do you actually get around that. If that's the right data to be showing someone or if that's accurate. And say the business decides, "Well we don't like that number." Many people feel pressured to then change the data, change, or change what the data shows. So I think being able to educate people to be able to find ways to say what the data is saying, but not going past some line where it's a lie, where it's unethical. 'Cause you can also say what data doesn't say. You don't always have to say what the data does say. You can leave it as, "Here's what we do know, "but here's what we don't know." There's a don't know part that many people will omit when they talk about data. So I think, you know especially when it comes to things like AI it's tricky, right? Because I always tell people I don't know everyone thinks AI's going to be so amazing. I started an industry by fixing problems with computers that people didn't realize computers had. For instance when you have a system, a lot of bugs, we all have bug reports that we've probably submitted. I mean really it's no where near the point where it's going to start dominating our lives and taking over all the jobs. Because frankly it's not that advanced. It's still run by people, still fixed by people, still managed by people. I think with ethics, you know a lot of it has to do with the regulations, what the laws say. That's really going to be what's involved in terms of what people are willing to do. A lot of businesses, they want to make money. If there's no rules that says they can't do certain things to make money, then there's no restriction. I think the other thing to think about is we as consumers, like everyday in our lives, we shouldn't separate the idea of data as a business. We think of it as a business person, from our day to day consumer lives. Meaning, yes I work with data. Incidentally I also always opt out of my credit card, you know when they send you that information, they make you actually mail them, like old school mail, snail mail like a document that says, okay I don't want to be part of this data collection process. Which I always do. It's a little bit more work, but I go through that step of doing that. Now if more people did that, perhaps companies would feel more incentivized to pay you for your data, or give you more control of your data. Or at least you know, if a company's going to collect information, I'd want you to be certain processes in place to ensure that it doesn't just get sold, right? For instance if a start up gets acquired what happens with that data they have on you? You agree to give it to start up. But I mean what are the rules on that? So I think we have to really think about the ethics from not just, you know, someone who's going to implement something but as consumers what control we have for our own data. 'Cause that's going to directly impact what businesses can do with our data. >> You know you mentioned data collection. So slightly on that subject. All these great new capabilities we have coming. We talked about what's going to happen with media in the future and what 5G technology's going to do to mobile and these great bandwidth opportunities. The internet of things and the internet of everywhere. And all these great inputs, right? Do we have an arms race like are we keeping up with the capabilities to make sense of all the new data that's going to be coming in? And how do those things square up in this? Because the potential is fantastic, right? But are we keeping up with the ability to make it make sense and to put it to use, Joe? >> So I think data ingestion and data integration is probably one of the biggest challenges. I think, especially as the world is starting to become more dependent on data. I think you know, just because we're dependent on numbers we've come up with GAAP, which is generally accepted accounting principles that can be audited and proven whether it's true or false. I think in our lifetime we will see something similar to that we will we have formal checks and balances of data that we use that can be audited. Getting back to you know what Dave was saying earlier about, I personally would trust a machine that was programmed to do the right thing, than to trust a politician or some leader that may have their own agenda. And I think the other thing about machines is that they are auditable. You know you can look at the code and see exactly what it's doing and how it's doing it. Human beings not so much. So I think getting to the truth, even if the truth isn't the answer that we want, I think is a positive thing. It's something that we can't do today that once we start relying on machines to do we'll be able to get there. >> Yeah I was just going to add that we live in exponential times. And the challenge is that the way that we're structured traditionally as organizations is not allowing us to absorb advances exponentially, it's linear at best. Everyone talks about change management and how are we going to do digital transformation. Evidence shows that technology's forcing the leaders and the laggards apart. There's a few leading organizations that are eating the world and they seem to be somehow rolling out new things. I don't know how Amazon rolls out all this stuff. There's all this artificial intelligence and the IOT devices, Alexa, natural language processing and that's just a fraction, it's just a tip of what they're releasing. So it just shows that there are some organizations that have path found the way. Most of the Fortune 500 from the year 2000 are gone already, right? The disruption is happening. And so we are trying, have to find someway to adopt these new capabilities and deploy them effectively or the writing is on the wall. I spent a lot of time exploring this topic, how are we going to get there and all of us have a lot of hard work is the short answer. >> I read that there's going to be more data, or it was predicted, more data created in this year than in the past, I think it was five, 5,000 years. >> Forever. (laughs) >> And that to mix the statistics that we're analyzing currently less than 1% of the data. To taking those numbers and hear what you're all saying it's like, we're not keeping up, it seems like we're, it's not even linear. I mean that gap is just going to grow and grow and grow. How do we close that? >> There's a guy out there named Chris Dancy, he's known as the human cyborg. He has 700 hundred sensors all over his body. And his theory is that data's not new, having access to the data is new. You know we've always had a blood pressure, we've always had a sugar level. But we were never able to actually capture it in real time before. So now that we can capture and harness it, now we can be smarter about it. So I think that being able to use this information is really incredible like, this is something that over our lifetime we've never had and now we can do it. Which hence the big explosion in data. But I think how we use it and have it governed I think is the challenge right now. It's kind of cowboys and indians out there right now. And without proper governance and without rigorous regulation I think we are going to have some bumps in the road along the way. >> The data's in the oil is the question how are we actually going to operationalize around it? >> Or find it. Go ahead. >> I will say the other side of it is, so if you think about information, we always have the same amount of information right? What we choose to record however, is a different story. Now if you want wanted to know things about the Olympics, but you decide to collect information every day for years instead of just the Olympic year, yes you have a lot of data, but did you need all of that data? For that question about the Olympics, you don't need to collect data during years there are no Olympics, right? Unless of course you're comparing it relative. But I think that's another thing to think about. Just 'cause you collect more data does not mean that data will produce more statistically significant results, it does not mean it'll improve your model. You can be collecting data about your shoe size trying to get information about your hair. I mean it really does depend on what you're trying to measure, what your goals are, and what the data's going to be used for. If you don't factor the real world context into it, then yeah you can collect data, you know an infinite amount of data, but you'll never process it. Because you have no question to ask you're not looking to model anything. There is no universal truth about everything, that just doesn't exist out there. >> I think she's spot on. It comes down to what kind of questions are you trying to ask of your data? You can have one given database that has 100 variables in it, right? And you can ask it five different questions, all valid questions and that data may have those variables that'll tell you what's the best predictor of Churn, what's the best predictor of cancer treatment outcome. And if you can ask the right question of the data you have then that'll give you some insight. Just data for data's sake, that's just hype. We have a lot of data but it may not lead to anything if we don't ask it the right questions. >> Joe. >> I agree but I just want to add one thing. This is where the science in data science comes in. Scientists often will look at data that's already been in existence for years, weather forecasts, weather data, climate change data for example that go back to data charts and so forth going back centuries if that data is available. And they reformat, they reconfigure it, they get new uses out of it. And the potential I see with the data we're collecting is it may not be of use to us today, because we haven't thought of ways to use it, but maybe 10, 20, even 100 years from now someone's going to think of a way to leverage the data, to look at it in new ways and to come up with new ideas. That's just my thought on the science aspect. >> Knowing what you know about data science, why did Facebook miss Russia and the fake news trend? They came out and admitted it. You know, we miss it, why? Could they have, is it because they were focused elsewhere? Could they have solved that problem? (crosstalk) >> It's what you said which is are you asking the right questions and if you're not looking for that problem in exactly the way that it occurred you might not be able to find it. >> I thought the ads were paid in rubles. Shouldn't that be your first clue (panelists laugh) that something's amiss? >> You know red flag, so to speak. >> Yes. >> I mean Bitcoin maybe it could have hidden it. >> Bob: Right, exactly. >> I would think too that what happened last year is actually was the end of an age of optimism. I'll bring up the Soviet Union again, (chuckles). It collapsed back in 1991, 1990, 1991, Russia was reborn in. And think there was a general feeling of optimism in the '90s through the 2000s that Russia is now being well integrated into the world economy as other nations all over the globe, all continents are being integrated into the global economy thanks to technology. And technology is lifting entire continents out of poverty and ensuring more connectedness for people. Across Africa, India, Asia, we're seeing those economies that very different countries than 20 years ago and that extended into Russia as well. Russia is part of the global economy. We're able to communicate as a global, a global network. I think as a result we kind of overlook the dark side that occurred. >> John: Joe? >> Again, the foolish optimist here. But I think that... It shouldn't be the question like how did we miss it? It's do we have the ability now to catch it? And I think without data science without machine learning, without being able to train machines to look for patterns that involve corruption or result in corruption, I think we'd be out of luck. But now we have those tools. And now hopefully, optimistically, by the next election we'll be able to detect these things before they become public. >> It's a loaded question because my premise was Facebook had the ability and the tools and the knowledge and the data science expertise if in fact they wanted to solve that problem, but they were focused on other problems, which is how do I get people to click on ads? >> Right they had the ability to train the machines, but they were giving the machines the wrong training. >> Looking under the wrong rock. >> (laughs) That's right. >> It is easy to play armchair quarterback. Another topic I wanted to ask the panel about is, IBM Watson. You guys spend time in the Valley, I spend time in the Valley. People in the Valley poo-poo Watson. Ah, Google, Facebook, Amazon they've got the best AI. Watson, and some of that's fair criticism. Watson's a heavy lift, very services oriented, you just got to apply it in a very focused. At the same time Google's trying to get you to click on Ads, as is Facebook, Amazon's trying to get you to buy stuff. IBM's trying to solve cancer. Your thoughts on that sort of juxtaposition of the different AI suppliers and there may be others. Oh, nobody wants to touch this one, come on. I told you elephant in the room questions. >> Well I mean you're looking at two different, very different types of organizations. One which is really spent decades in applying technology to business and these other companies are ones that are primarily into the consumer, right? When we talk about things like IBM Watson you're looking at a very different type of solution. You used to be able to buy IT and once you installed it you pretty much could get it to work and store your records or you know, do whatever it is you needed it to do. But these types of tools, like Watson actually tries to learn your business. And it needs to spend time doing that watching the data and having its models tuned. And so you don't get the results right away. And I think that's been kind of the challenge that organizations like IBM has had. Like this is a different type of technology solution, one that has to actually learn first before it can provide value. And so I think you know you have organizations like IBM that are much better at applying technology to business, and then they have the further hurdle of having to try to apply these tools that work in very different ways. There's education too on the side of the buyer. >> I'd have to say that you know I think there's plenty of businesses out there also trying to solve very significant, meaningful problems. You know with Microsoft AI and Google AI and IBM Watson, I think it's not really the tool that matters, like we were saying earlier. A fool with a tool is still a fool. And regardless of who the manufacturer of that tool is. And I think you know having, a thoughtful, intelligent, trained, educated data scientist using any of these tools can be equally effective. >> So do you not see core AI competence and I left out Microsoft, as a strategic advantage for these companies? Is it going to be so ubiquitous and available that virtually anybody can apply it? Or is all the investment in R&D and AI going to pay off for these guys? >> Yeah, so I think there's different levels of AI, right? So there's AI where you can actually improve the model. I remember when I was invited when Watson was kind of first out by IBM to a private, sort of presentation. And my question was, "Okay, so when do I get "to access the corpus?" The corpus being sort of the foundation of NLP, which is natural language processing. So it's what you use as almost like a dictionary. Like how you're actually going to measure things, or things up. And they said, "Oh you can't." "What do you mean I can't?" It's like, "We do that." "So you're telling me as a data scientist "you're expecting me to rely on the fact "that you did it better than me and I should rely on that." I think over the years after that IBM started opening it up and offering different ways of being able to access the corpus and work with that data. But I remember at the first Watson hackathon there was only two corpus available. It was either the travel or medicine. There was no other foundational data available. So I think one of the difficulties was, you know IBM being a little bit more on the forefront of it they kind of had that burden of having to develop these systems and learning kind of the hard way that if you don't have the right models and you don't have the right data and you don't have the right access, that's going to be a huge limiter. I think with things like medical, medical information that's an extremely difficult data to start with. Partly because you know anything that you do find or don't find, the impact is significant. If I'm looking at things like what people clicked on the impact of using that data wrong, it's minimal. You might lose some money. If you do that with healthcare data, if you do that with medical data, people may die, like this is a much more difficult data set to start with. So I think from a scientific standpoint it's great to have any information about a new technology, new process. That's the nice that is that IBM's obviously invested in it and collected information. I think the difficulty there though is just 'cause you have it you can't solve everything. And if feel like from someone who works in technology, I think in general when you appeal to developers you try not to market. And with Watson it's very heavily marketed, which tends to turn off people who are more from the technical side. Because I think they don't like it when it's gimmicky in part because they do the opposite of that. They're always trying to build up the technical components of it. They don't like it when you're trying to convince them that you're selling them something when you could just give them the specs and look at it. So it could be something as simple as communication. But I do think it is valuable to have had a company who leads on the forefront of that and try to do so we can actually learn from what IBM has learned from this process. >> But you're an optimist. (John laughs) All right, good. >> Just one more thought. >> Joe go ahead first. >> Joe: I want to see how Alexa or Siri do on Jeopardy. (panelists laugh) >> All right. Going to go around a final thought, give you a second. Let's just think about like your 12 month crystal ball. In terms of either challenges that need to be met in the near term or opportunities you think will be realized. 12, 18 month horizon. Bob you've got the microphone headed up, so I'll let you lead off and let's just go around. >> I think a big challenge for business, for society is getting people educated on data and analytics. There's a study that was just released I think last month by Service Now, I think, or some vendor, or Click. They found that only 17% of the employees in Europe have the ability to use data in their job. Think about that. >> 17. >> 17. Less than 20%. So these people don't have the ability to understand or use data intelligently to improve their work performance. That says a lot about the state we're in today. And that's Europe. It's probably a lot worse in the United States. So that's a big challenge I think. To educate the masses. >> John: Joe. >> I think we probably have a better chance of improving technology over training people. I think using data needs to be iPhone easy. And I think, you know which means that a lot of innovation is in the years to come. I do think that a keyboard is going to be a thing of the past for the average user. We are going to start using voice a lot more. I think augmented reality is going to be things that becomes a real reality. Where we can hold our phone in front of an object and it will have an overlay of prices where it's available, if it's a person. I think that we will see within an organization holding a camera up to someone and being able to see what is their salary, what sales did they do last year, some key performance indicators. I hope that we are beyond the days of everyone around the world walking around like this and we start actually becoming more social as human beings through augmented reality. I think, it has to happen. I think we're going through kind of foolish times at the moment in order to get to the greater good. And I think the greater good is using technology in a very, very smart way. Which means that you shouldn't have to be, sorry to contradict, but maybe it's good to counterpoint. I don't think you need to have a PhD in SQL to use data. Like I think that's 1990. I think as we evolve it's going to become easier for the average person. Which means people like the brain trust here needs to get smarter and start innovating. I think the innovation around data is really at the tip of the iceberg, we're going to see a lot more of it in the years to come. >> Dion why don't you go ahead, then we'll come down the line here. >> Yeah so I think over that time frame two things are likely to happen. One is somebody's going to crack the consumerization of machine learning and AI, such that it really is available to the masses and we can do much more advanced things than we could. We see the industries tend to reach an inflection point and then there's an explosion. No one's quite cracked the code on how to really bring this to everyone, but somebody will. And that could happen in that time frame. And then the other thing that I think that almost has to happen is that the forces for openness, open data, data sharing, open data initiatives things like Block Chain are going to run headlong into data protection, data privacy, customer privacy laws and regulations that have to come down and protect us. Because the industry's not doing it, the government is stepping in and it's going to re-silo a lot of our data. It's going to make it recede and make it less accessible, making data science harder for a lot of the most meaningful types of activities. Patient data for example is already all locked down. We could do so much more with it, but health start ups are really constrained about what they can do. 'Cause they can't access the data. We can't even access our own health care records, right? So I think that's the challenge is we have to have that battle next to be able to go and take the next step. >> Well I see, with the growth of data a lot of it's coming through IOT, internet of things. I think that's a big source. And we're going to see a lot of innovation. A new types of Ubers or Air BnBs. Uber's so 2013 though, right? We're going to see new companies with new ideas, new innovations, they're going to be looking at the ways this data can be leveraged all this big data. Or data coming in from the IOT can be leveraged. You know there's some examples out there. There's a company for example that is outfitting tools, putting sensors in the tools. Industrial sites can therefore track where the tools are at any given time. This is an expensive, time consuming process, constantly loosing tools, trying to locate tools. Assessing whether the tool's being applied to the production line or the right tool is at the right torque and so forth. With the sensors implanted in these tools, it's now possible to be more efficient. And there's going to be innovations like that. Maybe small start up type things or smaller innovations. We're going to see a lot of new ideas and new types of approaches to handling all this data. There's going to be new business ideas. The next Uber, we may be hearing about it a year from now whatever that may be. And that Uber is going to be applying data, probably IOT type data in some, new innovative way. >> Jennifer, final word. >> Yeah so I think with data, you know it's interesting, right, for one thing I think on of the things that's made data more available and just people we open to the idea, has been start ups. But what's interesting about this is a lot of start ups have been acquired. And a lot of people at start ups that got acquired now these people work at bigger corporations. Which was the way it was maybe 10 years ago, data wasn't available and open, companies kept it very proprietary, you had to sign NDAs. It was like within the last 10 years that open source all of that initiatives became much more popular, much more open, a acceptable sort of way to look at data. I think that what I'm kind of interested in seeing is what people do within the corporate environment. Right, 'cause they have resources. They have funding that start ups don't have. And they have backing, right? Presumably if you're acquired you went in at a higher title in the corporate structure whereas if you had started there you probably wouldn't be at that title at that point. So I think you have an opportunity where people who have done innovative things and have proven that they can build really cool stuff, can now be in that corporate environment. I think part of it's going to be whether or not they can really adjust to sort of the corporate, you know the corporate landscape, the politics of it or the bureaucracy. I think every organization has that. Being able to navigate that is a difficult thing in part 'cause it's a human skill set, it's a people skill, it's a soft skill. It's not the same thing as just being able to code something and sell it. So you know it's going to really come down to people. I think if people can figure out for instance, what people want to buy, what people think, in general that's where the money comes from. You know you make money 'cause someone gave you money. So if you can find a way to look at a data or even look at technology and understand what people are doing, aren't doing, what they're happy about, unhappy about, there's always opportunity in collecting the data in that way and being able to leverage that. So you build cooler things, and offer things that haven't been thought of yet. So it's a very interesting time I think with the corporate resources available if you can do that. You know who knows what we'll have in like a year. >> I'll add one. >> Please. >> The majority of companies in the S&P 500 have a market cap that's greater than their revenue. The reason is 'cause they have IP related to data that's of value. But most of those companies, most companies, the vast majority of companies don't have any way to measure the value of that data. There's no GAAP accounting standard. So they don't understand the value contribution of their data in terms of how it helps them monetize. Not the data itself necessarily, but how it contributes to the monetization of the company. And I think that's a big gap. If you don't understand the value of the data that means you don't understand how to refine it, if data is the new oil and how to protect it and so forth and secure it. So that to me is a big gap that needs to get closed before we can actually say we live in a data driven world. >> So you're saying I've got an asset, I don't know if it's worth this or this. And they're missing that great opportunity. >> So devolve to what I know best. >> Great discussion. Really, really enjoyed the, the time as flown by. Joe if you get that augmented reality thing to work on the salary, point it toward that guy not this guy, okay? (everyone laughs) It's much more impressive if you point it over there. But Joe thank you, Dion, Joe and Jennifer and Batman. We appreciate and Bob Hayes, thanks for being with us. >> Thanks you guys. >> Really enjoyed >> Great stuff. >> the conversation. >> And a reminder coming up a the top of the hour, six o'clock Eastern time, IBMgo.com featuring the live keynote which is being set up just about 50 feet from us right now. Nick Silver is one of the headliners there, John Thomas is well, or rather Rob Thomas. John Thomas we had on earlier on The Cube. But a panel discussion as well coming up at six o'clock on IBMgo.com, six to 7:15. Be sure to join that live stream. That's it from The Cube. We certainly appreciate the time. Glad to have you along here in New York. And until the next time, take care. (bright digital music)

(energetic music) >> Narrator: Live from Boston, Massachusetts it's the Cube, covering OpenStack Summit 2017 brought to you by the OpenStack Foundation, Red Hat, and additional ecosystem support. >> Hi and welcome back to SiliconANGLE TV's production of the Cube here at OpenStack Summit 2017 in Boston. I'm Stu Miniman joined with my co-host for the week, John Troyer. As you can see behind us, the day 2 keynotes letting out. John, it's always interesting to look at these shows. They had some demos that were awesome, a couple of demos were the demo gods were not smiling on them. They had Edward Snowden live via Q&A. They had Brian Stevens, who we're going to be talking with in a little bit, the CTO of Google, who was on The Early Start. For me, they're a little up and down. There's some of the vendor pitches in there, people are like, "Oh I have a great demo," and then you say, "Come to my booth "and see a bunch of my sessions." So, a little bit uneven and disjointed, which has been a some of the feedback you get about OpenStack in general over the last few years as to all those pieces come together. But yeah, what are your early thoughts coming out of the day 2 keynote? >> Well, it was definitely a keynote focused at the OpenStack community. We started off with open source and talking about the importance of open source, which is a little bit odd, because everyone here know that. I did like the message that OpenStack was composed of different projects, that it was a piece of the puzzle, not the whole puzzle. You and I both noted VMware's Scott Lowe tweeted, "It's good to the OpenStack Foundation talking about being a part of the overall solution, not the overall solution." I mean, as one example, they mentioned using etcd, which is a distributed key value store, instead of writing their own. Etcd powers Kubernetes. Your would be insane in 2017 to rewrite or distribute a key value pair, sorb at this point. Because, it's just out there, it's mature. You know, OpenStack has been around for seven years. There's been a lot of ecosystem grown up around them. >> Yeah, yeah. A couple of pieces on that. One is, there was a message about like, oh I can now take the individual components of OpenStack. I could actually do that before. I've noted, I've talked to a number of software companies, that when you did down into what they're doing, oh what do you know, there's, you know, there's Syndrr. Or, there's, you know, something in there, just as when I use AWS, I can use some of the individual components, same thing with OpenStack. It's not a monolith. There are the individual pieces. But, they're highlighting that a little bit more. They're saying use some of the pieces. The other thing, on the open source in general, they noted that like, in the artificial intelligence machine learning space, like, everyone that you see is using open source. Everything from Google and TensorFlow, is one that gets highlighted a lot. Amazon made a big push at their show about what they're doing with, you know, some of the machine learning. I can't remember right now, the program on there. But, right, in some of these emerging spaces, open source is the defacto way to do that. We had, in one of the conversations we had yesterday with one of the Cysco Distinguished Engineers, you know, it used to be standards. Now, open source really drives a lot of that. I actually got a quick conversation with Martin Casado, who had, you know, worked on a lot of open source things before Vmware acquired him. And, now he's at Andreessen Horowitz looking at all the open source models. So, unfortunately Martin didn't have enough time to come on the program, but we've had him on many times. Yeah, so sometime he's going to do that. >> Stu, I have a question. >> Stu: Yeah. >> The message today of being part of an ecosystem and being a componentized, open source set of projects, does that detract or add to this conversation around OpenStack Core versus Big Tent? >> I think Big Tent is dying. We talked to a number of the participants yesterday and said it was a little overblown. It does not mean that some pieces might still get worked on, but it's the core components. And you know, when dug into the survey, how many of the pieces do we really need? We want to make sure the Core works. I can have that distribution if I want to do what is OpenStack. When they highlighted those components, it wasn't 27 different projects there. You know, I think it was a handful of like six. >> Yeah. >> That were there. So, you know Swift and Syndrr, some interesting, cool little graphics. It was ironic, I tell you. The little graphic there, that was like a scary looking bear. It's like, I wouldn't want to run into him in a cartoon alley. Uh, but (laughs). >> Yeah, I did tweet. Yeah, there was an angry bear, kind of a poisonous spider, and a horse's behind. So, I'm not quite sure about the marketing there. But (laughs). >> What is the message you're sending? But, there's some fun. We've got, you know, Mark Collier and Jonathan Bryce coming on soon. We can ask them, you know, was this the community? And are there just some people that have a funny sense of humor, and this is how they show it? >> I did love the demos in today's talk, Stu. I especially liked, they spun up, live on stage, 15 from scratch, OpenStack clouds. And then, had them all join a CockroachDB cluster. I thought that was kind of cool and amazing. >> Yeah, absolutely. You talk about that hybrid, multi cloud world, showing it, you know, in reality, how that works. Pretty neat, and you know, you can actually see some applicability as to how that would fit into a customer environment. And, kudos to all the people. I mean, these were live, no net demos, not Camtasia, not some prerecorded things. Because like, oh wait, this thing's not quite ready to be able to be bootable, or you know, let me come in. I mean, they're up there on stage doing it. The wifi all seemed to work fine. That wasn't a challenge, but yeah, it was pretty cool. >> Well again, trying to give the message that OpenStack is indeed not a science project. That it's live, that it's configurable, that it's stable, that it's installable. And, I think that kind of message of stability, and configurability, and simplicity maybe is one of the ones they're trying to hit here today. >> Yeah, last thing I want to hit on, John, is I want to get your opinion. We throw out the term "open" a bunch. And, I'm watching some of the other industry things, and they say "open" when they mean "choice," as opposed to "open" as in "open source." So, you know, we see Google here, and Google talks about open. So many things that are now open source, a lot of times started out as a Google white paper or something. As we all say, we're all using open source which Google was using 10 years ago, right? You know, MapReduce, and Borg, and Spanner, and some of those things eventually get their way out. I've got some view points on this, but love to get your take first, yeah. >> Well, I mean, definitely it was an homage to open source this morning. In some ways, it was kind of a dig at AWS and Amazon, which uses a lot of open source tools, but does not share back. You know, OpenStack is clearly open source, and they were emphasizing that. I don't know. What are your thoughts, Stu? >> Yeah, it's, customers now, it used to be if you said open source, you know, go back 10, 15 years, and it was like, ooh, no. Now, open source is, a lot of times, a plus, something that they're asking for. Many companies are contributing and engaging in that. OpenStack is a great example of companies that have participated, you know, in helping to build OpenStack. That being said, you know, I always go to, you know, what's the problem to be solved, what's the solution that solves it. And, if it happens to be a little bit pre standard, or not 100% open source, most companies are fine with that. We were at Red Hat Summit last week with the Cube though, and everything they do is 100% open source. They're building their business. Their customers are really happy. So, you know, open source still has a little bit of a double edged sword as to how you do it. But, you know, open source absolutely, there's no question of if open source, it's how much, and to what extent, and where it fits. >> Sure, there is an ecosystem of providers here. There's always lock-in when you make a technical choice. But, in this case, I think they've successfully were trying to show off that there is a choice of clouds. There is an open, a set of open source components that you can mix and match. And so, that actually ties in very well to the interview with Edward Snowden. >> Yeah, absolutely, yeah. It was, and last point. Edward Snowden, towards the end he said fear is, I think the quote was, "the most powerful weapon in the world today." From a political statement, is what he's doing. Fear in IT is a powerful weapon. We know that, you know, enterprise and inertia, you know, tend to go together. With my background in networking, I used to draw these timelines. And, say, from when the time the standard was done to when, you know, the early majority adopt, is often times a decade. So, the technology adoption, moving the operational, we know the people piece is always tough to do, moving my applications. We think people are definitely moving faster, but fear is definitely something that holds them back. What do you see, john? >> Sure, I think the through line of the whole morning was about choice and diversity. Edward Snowden talked about the centralization of information services like Facebook, Google, and Twitter. And I think, and I think by implication, Amazon. And, I think the message that he was giving to the OpenStack crowd was look, you are enabling a multitude of services and a multitude of clouds, and that actually is a lever, a cultural lever against the over centralization of commercial forces, which are a little bit outside people's control. >> Yeah, so John, thanks for helping me wrap up day one. As always, we welcome our audience to please send us feedback. John and I are both pretty active on Twitter, very easy to get in touch with. We are at so many shows. You can check out SiliconANGLE TV. See where we're at. If we're not at a show that you think we should be at, reach, there's contact information at the top. If there's guests that we should have on our program, we're always looking for feedback. Love to get, especially those end user stories, talking about with interesting startups. So, we've got two more days of live coverage. So, for John and myself, stay with us. And, thanks, as always, for watching The Cube. (exciting music)

>>Fly from Houston, Texas. It's the cube covering Grace Hopper celebration of women in computing. >>Welcome back to the cubes coverage of the Grace Hopper conference here in Houston, Texas. I am your host, Rebecca Knight. We have a great panel today. Uh, three distinguished guests, Jeanette Epps, an aerospace astronaut. Uh, an engineer at NASA, Mimi Valdez, a executive producer on the film, hidden figures and Christina DOJ who is a, I want to call her a rocket scientist. She will not let me, she's an electrical engineer at, at, at NASA. Thank you so much for joining me. Hey Jeanette. I want to start with you. Um, recently president Obama has said we're gonna put men on Mars, men and women, men and women on Mars. How realistic is that? I mean, it's exciting for the, for the rest of us, non astronauts to hear this is, is it realistic? >>It is realistic. And one of the things I love that he, he did that was that it gives a national initiative to go back to Mars. And so that means that people will get more involved in STEM careers, especially girls will get more involved. And it's kinda like, you know what JFK did back in the 60s to give us that push a goal, an end goal to do something. Great. >>And do you think that, you know, he said by 2030, it's not very long from now. I mean, is it going to happen? I mean, what's, >>well right now a witness is working on is we have the NASA Orion program and it's a, uh, a power light capsule that will be launched off of one of the largest rockets bigger than the Saturn five or as big. And so that the mission of NASA, Orion is to take us beyond low earth orbit and go deeper into space. So we're looking at NASA, Orion, potentially maybe being the ship that will go to Mars and you know, maybe we have more work to do, but all of getting the nation onboard with going to Mars will inspire a new generation to do great things that will help us to get to Mars. Even >>Obama has said he loves science as a kid. That was his favorite subject in school. And do you think that it will have this galvanizing effect of, as you said, making sure more little boys and girls are studying STEM? >>Well, I've seen it already with some of the tweets and different things, questions that kids ask me nowadays. I think every kid has in their heart this goal to go to Mars now. And um, I can't go to a conference or anywhere without, uh, some young child asking about Mars and what, what are, how are we going to get there? When are we going to get there? And you know, I think one of my jobs is to inspire them to get involved in STEM and help us to get to Mars. There's a lot of technology that we need to develop and produce so that we can get astronauts to live longer away from the earth surface. We have the propulsion system that can get them there faster and bring them back home long. Will it take, well, it depends on the propulsion system that we developed. So there's a number of things that we're working on to make sure that what president Obama has said will get us to Mars in the 2030s if it's pushed out to a little later, that's fine. We're working on it and we're, we're going forward with them. >>Mimi, I want to talk to you now about the film hidden figures. Uh, we'll be out in some theaters and Christmas wide release in January. It is the story of black women mathematicians working in the 1960s at NASA. How did you find out about this story? Well, I give credits at Donna gelato, one of the producers on the film who optioned the book when it was a book proposal. So before the book was even written, she optioned this the story, and it's just this amazing story that the world doesn't even know about. We all know about John Glenn's mission. He came back a national hero. It was a moment in history that galvanized the world. You know, America winning the space race. But we don't know the story of all these brilliant mathematicians, all these women who actually will really responsible Katherine Johnson specifically who hand calculated those numbers for his cause. >>Everybody, I mean, I think this is such an amazing thing to do. And, and again, we just don't know her story. And as well as Dorothy Vaughn and Mary Jackson, I mean, so many women that worked at NASA that were just, um, they were hidden. You just don't know their stories. So, so the film tells their story, it tells their, um, it tells what they did, how they helped John Glenn. Did John Glenn appreciate that John Glenn actually would not go into space unless Katherine double checked the numbers. Like he wanted her to actually, you know, he, he, he trusted her because this is when the IBM computers were first coming into NASA. So they had started asserted use that and he was like, Hmm, I, I need Catherine to check the numbers before I go into say they were friends, professional colleagues. I mean he just knew who, you know, obviously she, she was really responsible and sort of that whole mission. >>And, and you know, for him it was just sort of like, eh, these computers thing, this was like a new thing at NASA. He's like, I need a human to make sure that these numbers are right. Right. Yeah. So we're excited about the film. Who's in it? Taraji P Henson plays captain Johnson. Octavia Spencer, please. I'm Dorothy Vaughan and Janell Monae. Um, she's a, uh, a musician. This is sort of her first really big role and she plays Mary Jackson. Kevin Costner is the head of the space station. Um, we have really great actors, but I think what was really important to everyone who participated in the film was everyone understood the importance of the story and wanting to make sure that we got it right. And also, you know, movies are supposed to be entertaining, but when they can be also inspirational and educate in some way, the fact that some young girls somewhere may see this movie and decide to pursue a career in math or science or any of the STEM careers is really gratifying to us because that's what we would love to accomplish. >>You know, Christina, you have been at NASA for nine years. Uh, tell me about your style, how you got, how you got to NASA in the first place. So I've always loved space since I was like a young child. I was in fifth grade when I told my parents that I wanted to work for NASA. So really since that point, like that was, you know, my dream. And so I, you know, pursued the math and science. Those were some of my favorite subjects. Um, luckily I had some supportive parents who really like saw that desire in me and kind of nurtured and encouraged me to, Hey, if that's what you want to do, then you go for it. We'll do whatever we can. Um, and then I came across some NASA opportunities in high school. Um, and one of the programs was the high school aerospace scholars program. >>And in that program I kinda got a glimpse into what it was like to be an engineer, to work at NASA. I got to speak with, you know, fight directors and um, flight controllers. And there's so many people who contribute to the space program. And that experience really solidified my desire to pursue STEM, STEM. Um, so I started to electrical engineering and then from there, um, you know, did the internship at NASA and I've enjoyed my career so far. It's been a, it's been a great experience. And so you work on the jet propulsion system of spaceships. Um, I work Lena. Um, I work on the power systems power systems. So you are, what do you do? So, um, as an electrical engineer on power systems, I work on the design of the power system testing. Um, basically everything on the spacecraft is going to need power. >>So I'm responsible for how I need to provide power, how much, um, when we talk about going to Mars, that's a, that's a long duration mission and power is something that, um, you have to budget for. So we need to advance that technology to support these missions that, um, our administration has said we want to go there. How are y'all going to accomplish this? So there's a lot of um, design hands on work and it's, you know, it's a challenge. But I mean, together as a team, we can, I believe that will, you know, meet that goal and be able to deliver a power system that will take us to Mars. So this is a question for rip for really all of you. You're an astronaut, you were working at NASA, you just made a movie to encourage young women to, to, to, to get into the STEM field. Why is it NASA recruiting here at, at, at Grace Hopper and, and should it be, do not, do you want to take this? >>Well, that's a good question. It's not that I'm mass and I don't, it's not that I don't think NASA has a desire to recruit here. I think there's recruiting times where people come out and do that. But I think I'm, one of the things that we do in the astronaut Corps, we try to go out and attend conferences like that and try to inspire students to be interested in NASA to understand what NASA is doing, to understand, you know, the shuttle retired. But we're still flying. In fact, when I fly to space and hopefully in 2018 I'll fly with the Russians. But in the meantime, NASA's building two shadows that would take astronauts to the international space station and NASA, Orion, that'll take us deeper into space. So we want to try to inspire with our stories and get people interested in science, technology, engineering, mathematics, and now even the arts, the arts play a big part of this. The arts play a big part of the well, yeah, I think I'm as a scientist and looking at patterns and things like that, there's a lot of um, people who, um, begin to work in the arts, even if it's building things with their hands and making, sculpting things, painting things. And so there's a lot of artwork that comes into play in science that is >>really refreshing, exciting, count, counterintuitive. I mean, what would you say are the ways we've talked about getting them, getting them interested through, through film. Um, talking about, uh, Obama making this, this grand announcement and Treme, what are some other ways that we can get the next generation into this field? Well, representation is obviously important. I think when people get to see images in the media of these different fields and all the possibilities, I mean every kid on this planet is obsessed with their phone, maybe not realizing like the importance of these STEM careers that are making these phones even possible or even exist. And I think the more that we can expose these careers and all these possibilities, I think it will just be just more beneficial just for humanity in general. I mean, as we know, nothing in this world can exist without math. >>Nothing. So the more that we can sort of encourage young people to see what an incredible career this is in all the possibilities that go into it, I just think we'll be better off as a nation and as a, you know, just globally as a world. Jeanette, I mean, do you have any thoughts about how, what you would advise someone? I mean you started at NASA nine years ago. So I mean, as an engineer I feel like, I mean I am making some contribution, but really the way I feel like I have more impact is through mentoring and you know, participating in those outreach type of activities for, uh, younger students like K through 12. And then also, um, you know, undergraduate like where they're really like trying to figure out what are the career options and STEM. And so that's how I feel I can have an impact there. >>And these movies help because there's a surge of like, like it's inspirational for young students to see this and be like, Oh, I never knew that that was an option. And so we get outreached to NASA, um, our request to, you know, interact with, uh, local schools and communities and kind of, um, you know, do all my lessons or just teaching with them, just talking about kind of like what the career is like. So, um, I mean I hoping that I can contribute in that way for younger, younger people. Janette are, you are an impressive astronaut, but you are also known as a black woman astronaut. Yeah. D do you do, do you bristle at that or do you embrace it? What, what do you, how, what's the responsibility? >>Oh, I totally embrace it. You know, I'm young ladies always ask me, did you have a problem being a black woman and engineering? And I always tell them that, um, I don't have a problem with being a black woman. And if other people do, then that's their problem. I totally embrace it because I'm, one of the things that I didn't realize was that, um, there's still a need to have positive role models and images of yourself. You know, growing up, my mom never taught my twin sister and I that you couldn't do something because you are a female or Brown. But there are a lot of young ladies that actually do experience that. And so having a positive roam out of it, show them that, Hey look, if I can do this, you can do this too. There's no reason you shouldn't be doing this right now yourself. >>So you are a role model. And how do you then also make sure that it's active role modeling and not just sort of standing on a pedestal of. >>One of the things I like to do is like Catherine Johnson and these great ladies that, you know, without them I, you know, I wouldn't be here is you have to do well and you have to perform well. You have to do the same work that your colleagues are doing and don't do less and don't accept less either. And when it comes to the hard work, put in the time, do the work, complete the tasks and make sure you're, you're representing yourself and your group well and you don't want to be accounted as well. You know, she's the one that we've got to help and we've got to do this, but you want to be a contributing member to every group that you're a part of and completing the tasks, doing the same work if not better. I like to say do better work, but you know, you want to be a part of the. >>Yeah. But that puts so much pressure too because it is, it's, it's be a contributor, but also don't mess up because you are under a microscope to some degree because those are, >>you know, messing up isn't, isn't. Um, failure is never, um, should never be. If it's unintentional, that's okay because you always learn from your mistakes and you have to forgive yourself and keep moving forward. If you stop right there because of a failure, um, you wouldn't go anywhere. We all fell. And it's how you respond to it. That matters. >>Yeah. Every failure is an opportunity to learn. And I think, um, you know, yeah. You can't be scared. I mean, the first and foremost is just doing a good job that, cause once, if you're just dedicated and focused on that, then I think great things can happen. And then failure is really a, a buzzword in Silicon Valley too. Right now. It's a fail fast. Um, and this idea, as you were talking about that it's your response to failure that makes a difference. Yeah. And NASA, I became familiar with this famous phrase of failing forward, meaning that yes, you're going to encounter problems, but if you are learning from the, if you're making improvements, you can design something better. So we call it failing forward. And that concept has, I've embraced that comset and it's, you know, I've encountered many failures. I mean, designing new hardware. It's not gonna, you know, work right off the box. And I'm kind of embracing that idea that it's a learning experience. As long as you don't give up as if you're applying what you learned, then that is not a failure. Christina, this is great. Christina DOJ, Mimi Valdez, Jeanette Epps. Thank you so much for joining us today. This has been such a having to be here. I'm not worthy. Thank you. This has been Rebecca Knight live coverage of the Grace Hopper conference here in Houston, Texas. We'll be back after this break.